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Prof. Dr. Robert Hable

  • Maschinelles Lernen
  • Datenanalyse / Statistik

Fakultät Angewandte Informatik

Professorinnen und Professoren

Professor

Studienfachberater BA Künstliche Intelligenz

K 003

0991/3615-745

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Beitrag in Sammelwerk/Tagungsband
  • Robert Hable

Data-Based Decisions under Imprecise Probability and Least Favorable Models.

  • And Supplements to the Article.

    • pg. 203-212

    (2007)

    Beitrag in Sammelwerk/Tagungsband
    • Robert Hable

    A Minimum Distance Estimator in an Imprecise Probability Model - Computational Aspects and Applications.

    (2009)

    Zeitschriftenartikel
    • Robert Hable

    Data-Based Decisions under Imprecise Probability and Least Favorable Models..

    In: International Journal of Approximate Reasoning (vol. 50) , pg. 642-654

    (2009)

    DOI: 10.1016/j.ijar.2008.03.009

    Abstract anzeigen

    Data-based decision theory under imprecise probability has to deal with optimization problems where direct solutions are often computationally intractable. Using the ΓΓ-minimax optimality criterion, the computational effort may significantly be reduced in the presence of a least favorable model. Buja [A. Buja, Simultaneously least favorable experiments. I. Upper standard functionals and sufficiency, Zeitschrift für Wahrscheinlichkeitstheorie und Verwandte Gebiete 65 (1984) 367–384] derived a necessary and sufficient condition for the existence of a least favorable model in a special case. The present article proves that essentially the same result is valid in case of general coherent upper previsions. This is done mainly by topological arguments in combination with some of Le Cam’s decision theoretic concepts. It is shown how least favorable models could be used to deal with situations where the distribution of the data as well as the prior is allowed to be imprecise.
    Beitrag in Sammelwerk/Tagungsband
    • T. Augustin
    • Robert Hable

    On the impact of robust statistics on imprecise probability models: a review.

    (2009)

    Zeitschriftenartikel
    • Robert Hable

    Finite approximations of data-based decision problems under imprecise probabilities..

    In: International Journal of Approximate Reasoning (vol. 50) , pg. 1115-1128

    (2009)

    DOI: 10.1016/j.ijar.2009.05.003

    Abstract anzeigen

    In decision theory under imprecise probabilities, discretizations are a crucial topic because many applications involve infinite sets whereas most procedures in the theory of imprecise probabilities can only be calculated for finite sets so far. The present paper develops a method for discretizing sample spaces in data-based decision theory under imprecise probabilities. The proposed method turns an original decision problem into a discretized decision problem. It is shown that any solution of the discretized decision problem approximately solves the original problem. In doing so, it is pointed out that the commonly used method of natural extension can be most instable. A way to avoid this instability is presented which is sufficient for the purpose of the paper.
    Beitrag in Sammelwerk/Tagungsband
    • D. Skulj
    • Robert Hable

    Coefficients of ergodicity for imprecise Markov chaines.

    (2009)

    Beitrag in Sammelwerk/Tagungsband
    • T. Kroupa
    • Robert Hable

    Structure of the Set of Belief Functions Generated by a Random Closed Interval.

    (2010)

    Zeitschriftenartikel
    • Robert Hable

    A Minimum Distance Estimator in an Imprecise Probability Model - Computational Aspects and Applications.

    In: International Journal of Approximate Reasoning (vol. 51) , pg. 1114-1128

    (2010)

    DOI: 10.1016/j.ijar.2010.08.003

    Abstract anzeigen

    The article considers estimating a parameter θ in an imprecise probability model View the MathML source(P¯θ)θ∈Θ which consists of coherent upper previsions View the MathML sourceP¯θ. After the definition of a minimum distance estimator in this setup and a summarization of its main properties, the focus lies on applications. It is shown that approximate minimum distances on the discretized sample space can be calculated by linear programming. After a discussion of some computational aspects, the estimator is applied in a simulation study consisting of two different models. Finally, the estimator is applied on a real data set in a linear regression model.
    Zeitschriftenartikel
    • T. Augustin
    • Robert Hable

    On the impact of robust statistics on imprecise probability models: a review.

    In: Structural Safety (vol. 32) , pg. 358-365

    (2010)

    DOI: 10.1016/j.strusafe.2010.06.002

    Abstract anzeigen

    Robust statistics is concerned with statistical methods that still lead to reliable conclusions if an ideal model is only approximately true. More recently, the theory of imprecise probabilities was developed as a general methodology to model non-stochastic uncertainty (ambiguity) adequately, and has been successfully applied to many engineering problems. In robust statistics, small deviations from ideal models are modeled by certain neighborhoods. Since nearly all commonly used neighborhoods are imprecise probabilities, a large part of robust statistics can be seen as a special case of imprecise probabilities. Therefore, it seems quite promising to address problems in the theory of imprecise probabilities by trying to generalize results of robust statistics. In this review paper, we present some cases where this has already been done successfully and where the connections between (frequentist) robust statistics and imprecise probabilities are most striking.
    Zeitschriftenartikel
    • Robert Hable

    Minimum Distance Estimation in Imprecise Probability Models.

    In: Journal of Statistical Planning and Inference (vol. 140) , pg. 461-479

    (2010)

    Abstract anzeigen

    The present article considers estimating a parameter θθ in an imprecise probability model View the MathML source(P¯θ)θ∈Θ. This model consists of coherent upper previsions View the MathML sourceP¯θ which are given by finite numbers of constraints on expectations. A minimum distance estimator is defined in this case and its asymptotic properties are investigated. It is shown that the minimum distance can be approximately calculated by discretizing the sample space. Finally, the estimator is applied in a simulation study and on a real data set.
    Zeitschriftenartikel
    • Robert Hable
    • P. Ruckdeschel
    • H. Rieder

    Optimal robust influence functions in semiparametric regression.

    In: Journal of Statistical Planning and Inference (vol. 140) , pg. 226-245

    (2010)

    DOI: 10.1016/j.jspi.2009.07.010

    Abstract anzeigen

    Robust statistics allows the distribution of the observations to be any member of a suitable neighborhood about an ideal model distribution. In this paper, the ideal models are semiparametric with finite-dimensional parameter of interest and a possibly infinite-dimensional nuisance parameter. In the asymptotic setup of shrinking neighborhoods, we derive and study the Hampel-type problem and the minmax MSE-problem. We show that, for all common types of neighborhood systems, the optimal influence function View the MathML sourceψ˜ can be approximated by the optimal influence functions View the MathML sourceψ˜n for certain parametric models. For general semiparametric regression models, we determine View the MathML source(ψ˜n)n∈N in case of error-in-variables and in case of error-free-variables. Finally, the results are applied to Cox regression where we compare our approach to that of Bednarski [1993. Robust estimation in Cox's regression model. Scand. J. Statist. 20, 213–225] in a small simulation study and on a real data set.
    Beitrag in Sammelwerk/Tagungsband
    • M. Troffaes
    • Robert Hable

    Robustness of Natural Extension.

    • In:
    • F. Coolen
    • G. Cooman
    • M. Oberguggenberger
    • T. Fetz

    (2011)

    Zeitschriftenartikel
    • Robert Hable
    • A. Christmann

    On Qualitative Robustness of Support Vector Machines.

    In: Journal of Multivariate Analysis (vol. 102) , pg. 993-1007

    (2011)

    DOI: 10.1016/j.jmva.2011.01.009

    Abstract anzeigen

    Support vector machines (SVMs) have attracted much attention in theoretical and in applied statistics. The main topics of recent interest are consistency, learning rates and robustness. We address the open problem whether SVMs are qualitatively robust. Our results show that SVMs are qualitatively robust for any fixed regularization parameter λλ. However, under extremely mild conditions on the SVM, it turns out that SVMs are not qualitatively robust any more for any null sequence λnλn, which are the classical sequences needed to obtain universal consistency. This lack of qualitative robustness is of a rather theoretical nature because we show that, in any case, SVMs fulfill a finite sample qualitative robustness property. For a fixed regularization parameter, SVMs can be represented by a functional on the set of all probability measures. Qualitative robustness is proven by showing that this functional is continuous with respect to the topology generated by weak convergence of probability measures. Combined with the existence and uniqueness of SVMs, our results show that SVMs are the solutions of a well-posed mathematical problem in Hadamard’s sense.
    Zeitschriftenartikel
    • Robert Hable

    Asymptotic Normality of Support Vector Machine Variants and Other Regularized Kernel Methods.

    In: Journal of Multivariate Analysis (vol. 106) , pg. 92-117

    (2012)

    DOI: 10.1016/j.jmva.2011.11.004

    Abstract anzeigen

    In nonparametric classification and regression problems, regularized kernel methods, in particular support vector machines, attract much attention in theoretical and in applied statistics. In an abstract sense, regularized kernel methods (simply called SVMs here) can be seen as regularized M-estimators for a parameter in a (typically infinite dimensional) reproducing kernel Hilbert space. For smooth loss functions LL, it is shown that the difference between the estimator, i.e. the empirical SVM View the MathML sourcefL,Dn,λDn, and the theoretical SVM fL,P,λ0fL,P,λ0 is asymptotically normal with rate View the MathML sourcen. That is, View the MathML sourcen(fL,Dn,λDn−fL,P,λ0) converges weakly to a Gaussian process in the reproducing kernel Hilbert space. As common in real applications, the choice of the regularization parameter View the MathML sourceDn in View the MathML sourcefL,Dn,λDn may depend on the data. The proof is done by an application of the functional delta-method and by showing that the SVM-functional P↦fL,P,λP↦fL,P,λ is suitably Hadamard-differentiable.
    Zeitschriftenartikel
    • A. Christmann
    • Robert Hable

    Consistency of support vector machines using additive kernels for additive models.

    In: Computational Statistics & Data Analysis (vol. 56) , pg. 854-873

    (2012)

    DOI: 10.1016/j.csda.2011.04.006

    Abstract anzeigen

    Support vector machines (SVMs) are special kernel based methods and have been among the most successful learning methods for more than a decade. SVMs can informally be described as kinds of regularized MM-estimators for functions and have demonstrated their usefulness in many complicated real-life problems. During the last few years a great part of the statistical research on SVMs has concentrated on the question of how to design SVMs such that they are universally consistent and statistically robust for nonparametric classification or nonparametric regression purposes. In many applications, some qualitative prior knowledge of the distribution View the MathML sourceP or of the unknown function ff to be estimated is present or a prediction function with good interpretability is desired, such that a semiparametric model or an additive model is of interest. The question of how to design SVMs by choosing the reproducing kernel Hilbert space (RKHS) or its corresponding kernel to obtain consistent and statistically robust estimators in additive models is addressed. An explicit construction of such RKHSs and their kernels, which will be called additive kernels, is given. SVMs based on additive kernels will be called additive support vector machines . The use of such additive kernels leads, in combination with a Lipschitz continuous loss function, to SVMs with the desired properties for additive models. Examples include quantile regression based on the pinball loss function, regression based on the ϵϵ-insensitive loss function, and classification based on the hinge loss function.
    Beitrag in Sammelwerk/Tagungsband
    • A. Christmann
    • Robert Hable

    On the Bootstrap Approach for Support Vector Machines and Related Kernel Based Methods.

    (2013)

    Zeitschriftenartikel
    • Robert Hable

    Universal Consistency of Localized Versions of Regularized Kernel Methods.

    In: Journal of Machine Learning Research (vol. 14) , pg. 111-144

    (2013)

    Abstract anzeigen

    In supervised learning problems, global and local learning algorithms are used. In contrast to global learning algorithms, the prediction of a local learning algorithm in a testing point is only based on training data which are close to the testing point. Every global algorithm such as support vector machines (SVM) can be localized in the following way: in every testing point, the (global) learning algorithm is not applied to the whole training data but only to the k nearest neighbors (kNN) of the testing point. In case of support vector machines, the success of such mixtures of SVM and kNN (called SVM-KNN) has been shown in extensive simulation studies and also for real data sets but only little has been known on theoretical properties so far. In the present article, it is shown how a large class of regularized kernel methods (including SVM) can be localized in order to get a universally consistent learning algorithm.
    Zeitschriftenartikel
    • D. Skulj
    • Robert Hable

    Coefficients of ergodicity for Markov chains with uncertain parameters.

    In: Metrika (vol. 76) , pg. 107-133

    (2013)

    DOI: 10.1007/s00184-011-0378-0

    Abstract anzeigen

    ne of the central considerations in the theory of Markov chains is their convergence to an equilibrium. Coefficients of ergodicity provide an efficient method for such an analysis. Besides giving sufficient and sometimes necessary conditions for convergence, they additionally measure its rate. In this paper we explore coefficients of ergodicity for the case of imprecise Markov chains. The latter provide a convenient way of modelling dynamical systems where parameters are not determined precisely. In such cases a tool for measuring the rate of convergence is even more important than in the case of precisely determined Markov chains, since most of the existing methods of estimating the limit distributions are iterative. We define a new coefficient of ergodicity that provides necessary and sufficient conditions for convergence of the most commonly used class of imprecise Markov chains. This so-called weak coefficient of ergodicity is defined through an endowment of the structure of a metric space to the class of imprecise probabilities. Therefore we first make a detailed analysis of the metric properties of imprecise probabilities.
    Zeitschriftenartikel
    • B. Mislimshoeva
    • Robert Hable
    • C. Samimi
    • A. Abdulnazarov
    • M. Fezakov
    • T. Koellner

    Factors Influencing Households' Firewood Consumption in the Western Pamirs, Tajikistan.

    In: Mountain Research and Development (vol. 34) , pg. 147-156

    (2014)

    DOI: 10.1659/MRD-JOURNAL-D-13-00113.1

    Abstract anzeigen

    Firewood is a major energy source, especially in many high mountainous regions in developing countries where other energy sources are limited. In the mountainous regions of Tajikistan, current energy consumption is limited owing to geographic isolation and numerous challenges—including in the energy sector—that emerged after the collapse of the Soviet Union and Tajikistan's independence. The sudden disruption of external supplies of energy forced people to rely on locally available but scarce biomass resources, such as firewood and animal dung. We conducted an empirical study to gain an understanding of current household energy consumption in the Western Pamirs of Tajikistan and the factors that influence firewood consumption. For this purpose, we interviewed members of 170 households in 8 villages. We found that, on average, households consumed 355 kg of firewood, 253 kWh of electricity, 760 kg of dung, and 6 kg of coal per month in the winter of 2011–2012. Elevation, size of a household's private garden, and total hours of heating had a positive relationship with firewood consumption, and education level and access to a reliable supply of electricity showed a negative relationship.
    Zeitschriftenartikel
    • Robert Hable
    • A. Christmann

    Estimation of Scale Functions to Model Heteroscedasticity by Kernel Based Quantile Methods.

    In: Journal of Nonparametric Statistics (vol. 26) , pg. 219-239

    (2014)

    DOI: 10.1080/10485252.2013.875547

    Abstract anzeigen

    A main goal of regression is to derive statistical conclusions on the conditional distribution of the output variable Y given the input values x. Two of the most important characteristics of a single distribution are location and scale. Regularised kernel methods (RKMs) – also called support vector machines in a wide sense – are well established to estimate location functions like the conditional median or the conditional mean. We investigate the estimation of scale functions by RKMs when the conditional median is unknown, too. Estimation of scale functions is important, e.g. to estimate the volatility in finance. We consider the median absolute deviation (MAD) and the interquantile range as measures of scale. Our main result shows the consistency of MAD-type RKMs.
    Vortrag
    • Robert Hable

    Nichtparametrische Klassifikation und Regression mit SVMs und anderen regularisierten Kern-Verfahren: Statistische Modelle und Inferenz.

    Lübeck 14.11.2014.

    (2014)

    Monographie
    • Robert Hable

    Einführung in die Stochastik. Ein Begleitbuch zur Vorlesung.

    Berlin [u.a.]: Springer

    (2015)

    Zeitschriftenartikel
    • A.-L. Boulesteix
    • Robert Hable
    • S. Lauer
    • M.J.A. Eugster

    A Statistical Framework for Hypothesis Testing in Real Data Comparison Studies.

    In: The American Statistician (vol. 69) , pg. 201-212

    (2015)

    DOI: 10.1080/00031305.2015.1005128

    Abstract anzeigen

    In computational sciences, including computational statistics, machine learning, and bioinformatics, it is often claimed in articles presenting new supervised learning methods that the new method performs better than existing methods on real data, for instance in terms of error rate. However, these claims are often not based on proper statistical tests and, even if such tests are performed, the tested hypothesis is not clearly defined and poor attention is devoted to the Type I and Type II errors. In the present article, we aim to fill this gap by providing a proper statistical framework for hypothesis tests that compare the performances of supervised learning methods based on several real datasets with unknown underlying distributions. After giving a statistical interpretation of ad hoc tests commonly performed by computational researchers, we devote special attention to power issues and outline a simple method of determining the number of datasets to be included in a comparison study to reach an adequate power. These methods are illustrated through three comparison studies from the literature and an exemplary benchmarking study using gene expression microarray data. All our results can be reproduced using R codes and datasets available from the companion website http://www.ibe.med.uni-muenchen.de/organisation/mitarbeiter/020_professuren/boulesteix/compstud2013.
    Zeitschriftenartikel
    • O. Fishkis
    • M. Wachten
    • Robert Hable

    Assessment of soil water repellency as a function of soil moisture with mixed modelling.

    In: European Journal of Soil Science (vol. 66) , pg. 910-920

    (2015)

    DOI: 10.1111/ejss.12283

    Abstract anzeigen

    An understanding of the relation between soil water repellency (SWR) and soil moisture is a prerequisite of water-flow modelling in water-repellent soil. Here, the relation between SWR and soil moisture was investigated with intact cores of soil taken from three types of soil with different particle-size distributions. The SWR was measured by a sessile drop contact angle (CA) during drying at soil pF values that ranged from −∞ to 4.2. From the measured CA, the work of adhesion (Wa) was calculated and its relation with the pF-value was explored. Mixed modelling was applied to evaluate the effects of pF, soil type and soil depth on CA and Wa. For all soil types, a positive relation was observed between CA and the pF-value that could be represented by a linear model for the pF-range of 1–4.2. The variation in slope and intercept of the CA–pF relationship caused by heterogeneity of the samples taken from a single soil horizon was quantified. In addition, the relation between CA and water content (WC) showed hysteresis, with significantly larger CAs during drying than during wetting.
    Vortrag
    • Robert Hable

    Statistical Properties of Support Vector Machines and Related Methods from Machine Learning: Theory and Applications.

    Jindřichův Hradec, Tschechische Republik 02.-03.07.2015.

    (2015)

    Vortrag
    • Robert Hable

    Maschinelles Lernen: Datenanalyse mit Methoden der künstlichen Intelligenz. Gastvortrag in Vorlesung zu "Big Data-Algorithms and Systems".

    • Hochschule Landshut.

    Landshut 07.07.2015.

    (2015)

    Vortrag
    • Robert Hable

    Nichtparametrische Klassifikation und Regression mit maschinellen Lernverfahren: Theorie und Anwendungen.

    • Fraunhofer-Institut für Techno- und Wirtschaftsmathematik.

    Kaiserslautern 03.08.2015.

    (2015)

    Zeitschriftenartikel
    • H. Albrecht
    • J. Gallitz
    • Robert Hable
    • M. Vieth
    • G. Tontini
    • M. Neurath
    • J. Riemann
    • H. Neumann

    The Offer of Advanced Imaging Techniques Leads to Higher Acceptance Rates for Screening Colonoscopy - A Prospective Multivariate Analysis of Data From a Patient Questionnaire.

    In: Gastrointestinal Endoscopy (vol. 83) , pg. AB359-AB360

    (2016)

    DOI: 10.1016/j.gie.2016.03.916

    Zeitschriftenartikel
    • O. Fishkis
    • K. Müller
    • Robert Hable
    • B. Huwe

    Effects of Throughfall Exclusion, Soil Texture and Spatial Continuity on Soil Water Repellency in Fichtel Mountains.

    In: Soil Science Society of America Journal (vol. 80) , pg. 554-562

    (2016)

    DOI: 10.2136/sssaj2015.10.0386

    Abstract anzeigen

    The occurrence of soil water repellency (SWR) in soil is controlled by soil organic matter (SOM) composition and is strongly soil-moisture dependent. During drying the reduction of water content in soil has been shown to induce the outward orientation of nonpolar ends of organic compounds and hence the increase in SWR. A prolonged drought can however also induce changes in SOM composition which in turn can affect SWR. In this study, we eliminate differences in water content after prolonged throughfall exclusion and a control treatment by oven-drying of the soil samples, to test if a prolonged drought affects SWR even after excluding the direct effect of soil moisture. In addition, the relevance of soil texture variability and spatial dependence of SWR for prediction of soil wettability distribution over the study area was explored. The samples of the upper mineral soil horizon were taken from six plots in Fichtel Mountains, subjected to a throughfall exclusion or control treatments, oven-dried and analyzed for soil texture and water drop penetration time (WDPT). A linear model with spatially correlated random effects was used to quantify the effects of soil texture and treatment on the persistence of the SWR and to simultaneously evaluate the spatial structure of the SWR. Based on estimated parameters the persistence of SWR was calculated on unsampled locations by robust kriging with external drift. The throughfall exclusion treatment significantly increased the log(WDPT) (p < 0.01) of the oven-dried soil by 0.46. The clay content and the sand content had highly significant (p < 0.001) negative effects, while silt content had positive effects on the log(WDPT). The variogram parameter with a range of 5.2 m, a nugget of 0.25, and a sill of 0.45 indicated a rather low degree of spatial dependence of log(WDPT). The main outcome of this study is that the positive effect of throughfall exclusion on SWR cannot be fully attributed to water content reduction. Most probably the drought-induced changes in SOM composition and microbial community were responsible for the observed increase in SWR.
    Zeitschriftenartikel
    • H. Albrecht
    • J. Gallitz
    • Robert Hable
    • M. Vieth
    • G. Tontini
    • M. Neurath
    • J. Riemann
    • H. Neumann

    The Offer of Advanced Imaging Techniques Leads to Higher Acceptance Rates for Screening Colonoscopy - a Prospective Study.

    In: Asian Pacific Journal of Cancer Prevention (vol. 17) , pg. 3871-3875

    (2016)

    Abstract anzeigen

    Colonoscopy plays a fundamental role in early diagnosis and management of colorectal cancer and requires public and professional acceptance to ensure the ongoing success of screening programs. The aim of the study was to prospectively assess whether patient acceptance rates to undergo screening colonoscopy could be improved by the offer of advanced imaging techniques. Materials and Methods Overall, 372 randomly selected patients were prospectively included. A standardized questionnaire was developed that inquired of the patients their knowledge regarding advanced imaging techniques. Second, several media campaigns and information events were organized reporting about advanced imaging techniques, followed by repeated evaluation. After one year the evaluation ended. Results At baseline, 64% of the patients declared that they had no knowledge about new endoscopic methods. After twelve months the overall grade of information increased signi cantly from 14% at baseline to 34%. The percentage of patients who decided to undergo colonoscopy because of the offer of new imaging methods also increased signi cantly from 12% at baseline to 42% after 12 months. Conclusions Patients were highly interested in the offer of advanced imaging techniques. Knowledge about these techniques could relatively easy be provided using local media campaigns. The offer of advanced imaging techniques leads to higher acceptance rates for screening colonoscopies.
    Zeitschriftenartikel
    • K. Strohriegel
    • Robert Hable

    Qualitative robustness of estimators on stochastic processes.

    In: Metrika (vol. 79) , pg. 895-917

    (2016)

    DOI: 10.1007/s00184-016-0582-z

    Abstract anzeigen

    A lot of statistical methods originally designed for independent and identically distributed (i.i.d.) data are also successfully used for dependent observations. Still most theoretical investigations on robustness assume i.i.d. pairs of random variables. We examine an important property of statistical estimators—the qualitative robustness in the case of observations which do not fulfill the i.i.d. assumption. In the i.i.d. case qualitative robustness of a sequence of estimators is, according to Hampel (Ann Math Stat 42:1887–1896, 1971), ensured by continuity of the corresponding statistical functional. A similar result for the non-i.i.d. case is shown in this article. Continuity of the corresponding statistical functional still ensures qualitative robustness of the estimator as long as the data generating process satisfies a certain convergence condition on its empirical measure. Examples for processes providing such a convergence condition, including certain Markov chains or mixing processes, are given as well as examples for qualitatively robust estimators in the non-i.i.d. case.
    Zeitschriftenartikel
    • Nari Arunraj
    • Robert Hable
    • Michael Fernandes
    • Karl Leidl
    • Michael Heigl

    Comparison of Supervised, Semi-supervised and Unsupervised Learning Methods in Network Intrusion Detection Systems (NIDS) Application.

    In: Anwendungen und Konzepte in der Wirtschaftsinformatik (AKWI) , pg. 10-19

    (2017)

    Abstract anzeigen

    With the emergence of the fourth industrial revolution (Industrie 4.0) of cyber physical systems, intrusion detection systems are highly necessary to detect industrial network attacks. Recently, the increase in application of specialized machine learning techniques is gaining critical attention in the intrusion detection community. A wide variety of learning techniques proposed for different network intrusion detection system (NIDS) problems can be roughly classified into three broad categories: supervised, semi-supervised and unsupervised. In this paper, a comparative study of selected learning methods from each of these three kinds is carried out. In order to assess these learning methods, they are subjected to investigate network traffic datasets from an Airplane Cabin Demonstrator. In addition to this, the imbalanced classes (normal and anomaly classes) that are present in the captured network traffic data is one of the most crucial issues to be taken into consideration. From this investigation, it has been identified that supervised learning methods (logistic and lasso logistic regression methods) perform better than other methodswhen historical data on former attacks are available. The results of this study have also showed that the performance of semi-supervised learning method (One class support vector machine) is comparatively better than unsupervised learning method (Isolation Forest) when historical data on former attacks are not available.
    Zeitschriftenartikel
    • C. Dupke
    • C. Bonenfant
    • B. Reineking
    • Robert Hable
    • T. Zeppenfeld
    • M. Ewald
    • M. Heurich

    Habitat selection by a large herbivore at multiple spatial and temporal scales is primarily governed by food resources.

    In: Ecography - Pattern and Process in Ecology (vol. 40) , pg. 1014-1027

    (2017)

    DOI: 10.1111/ecog.02152

    Abstract anzeigen

    Habitat selection can be considered as a hierarchical process in which animals satisfy their habitat requirements at different ecological scales. Theory predicts that spatial and temporal scales should co‐vary in most ecological processes and that the most limiting factors should drive habitat selection at coarse ecological scales, but be less influential at finer scales. Using detailed location data on roe deer Capreolus capreolus inhabiting the Bavarian Forest National Park, Germany, we investigated habitat selection at several spatial and temporal scales. We tested 1) whether time‐varying patterns were governed by factors reported as having the largest effects on fitness, 2) whether the trade‐off between forage and predation risks differed among spatial and temporal scales and 3) if spatial and temporal scales are positively associated. We analysed the variation in habitat selection within the landscape and within home ranges at monthly intervals, with respect to land‐cover type and proxys of food and cover over seasonal and diurnal temporal scales. The fine‐scale temporal variation follows a nycthemeral cycle linked to diurnal variation in human disturbance. The large‐scale variation matches seasonal plant phenology, suggesting food resources being a greater limiting factor than lynx predation risk. The trade‐off between selection for food and cover was similar on seasonal and diurnal scale. Habitat selection at the different scales may be the consequence of the temporal variation and predictability of the limiting factors as much as its association with fitness. The landscape of fear might have less importance at the studied scale of habitat selection than generally accepted because of the predator hunting strategy. Finally, seasonal variation in habitat selection was similar at the large and small spatial scales, which may arise because of the marked philopatry of roe deer. The difference is supposed to be greater for wider ranging herbivores.
    Vortrag
    • Robert Hable

    Big Data - erste Schritte wagen! Praxisbeispiele und Handlungsempfehlungen für Unternehmen.

    • Strategische Partnerschaft Sensorik e.V..

    Regensburg 27.09.2017.

    (2017)

    Vortrag
    • Robert Hable

    Prognosen in Unternehmen: Praxisbeispiele und Handlungsempfehlungen.

    Grafenau 06.11.2017.

    (2017)

    Vortrag
    • Robert Hable

    Big Data Analytics im Unternehmen: Strategien, Praxisbeispiele und Methoden.

    Frankfurt am Main 04.12.2017.

    (2017)

    Vortrag
    • Robert Hable

    Statistische Daten in der Praxis: Zeitverschwendung oder Goldgrube?.

    • Bayerisches Landwirtschaftsministerium.

    München 20.02.2018.

    (2018)

    Vortrag
    • Robert Hable

    BIG DATA in der Großküche - Was steckt dahinter, wo liegen die Chancen und Risiken?.

    Berlin 16.04.2018.

    (2018)

    Vortrag
    • Robert Hable

    What Machine Learning Can Do.

    München 14.05.2018.

    (2018)

    Vortrag
    • Robert Hable

    Big Data in der Produktion.

    • Cluster Mechatronik Akademie.

    Regensburg 27.11.2018.

    (2018)

    Vortrag
    • Robert Hable

    Maschinelles Lernen erfolgreich nutzen.

    • Technische Hochschule Deggendorf.

    Deggendorf 16.01.2019.

    (2019)

    Vortrag
    • Robert Hable

    Fitting Additive Models With Regularized Kernel Methods: Methodology, Robustness Properties, and Business Applications.

    • Ludwig-Maximilians-Universität.

    München 20.03.2019.

    (2019)

    Zeitschriftenartikel
    • Michael Heigl
    • Kumar Anand
    • Andreas Urmann
    • D. Fiala
    • Martin Schramm
    • Robert Hable

    On the Improvement of the Isolation Forest Algorithm for Outlier Detection with Streaming Data.

    In: Electronics (vol. 10) , pg. 1534

    (2021)

    DOI: 10.3390/electronics10131534

    Abstract anzeigen

    In recent years, detecting anomalies in real-world computer networks has become a more and more challenging task due to the steady increase of high-volume, high-speed and high-dimensional streaming data, for which ground truth information is not available. Efficient detection schemes applied on networked embedded devices need to be fast and memory-constrained, and must be capable of dealing with concept drifts when they occur. Different approaches for unsupervised online outlier detection have been designed to deal with these circumstances in order to reliably detect malicious activity. In this paper, we introduce a novel framework called PCB-iForest, which generalized, is able to incorporate any ensemble-based online OD method to function on streaming data. Carefully engineered requirements are compared to the most popular state-of-the-art online methods with an in-depth focus on variants based on the widely accepted isolation forest algorithm, thereby highlighting the lack of a flexible and efficient solution which is satisfied by PCB-iForest. Therefore, we integrate two variants into PCB-iForest—an isolation forest improvement called extended isolation forest and a classic isolation forest variant equipped with the functionality to score features according to their contributions to a sample’s anomalousness. Extensive experiments were performed on 23 different multi-disciplinary and security-related real-world datasets in order to comprehensively evaluate the performance of our implementation compared with off-the-shelf methods. The discussion of results, including AUC, F1 score and averaged execution time metric, shows that PCB-iForest clearly outperformed the state-of-the-art competitors in 61% of cases and even achieved more promising results in terms of the tradeoff between classification and computational costs.
    Vortrag
    • Robert Hable

    Künstliche Intelligenz – was bringt es dem Mittelstand?.

    • EUREGIO Bayerischer Wald - Böhmerwald - Unterer Inn.

    Online 30.03.2021.

    (2021)

    Vortrag
    • Robert Hable

    KI in der Produktion – Methoden, Praxisbeispiele, Strategien.

    • Cluster Mechatronik & Automation.

    Online 11.06.2021.

    (2021)

    Vortrag
    • Robert Hable

    Best Practice Projekt: Internationales Big Data Zentrum Ostbayern-Südböhmen.

    • Europaregion Donau-Moldau e.V..

    Online 08.10.2021.

    (2021)

    Ton-/Filmdokument
    • Robert Hable

    Podiumsdiskussion des Q2-Leistungskurses Geographie des Gymnasiums Siegburg Alleestraße: Die Stadt als lebenswerter Raum für alle? - Strategien einer zukunftsorientierten Stadtentwicklung.

    (2022)

    Vortrag
    • Robert Hable

    KI in der Produktion – Methoden, Praxisbeispiele, Strategien.

    • Cluster Mechatronik & Automation.

    Online 01.04.2022.

    (2022)

    Vortrag
    • Robert Hable

    Fragebögen erstellen und auswerten - (k)eine Wissenschaft für sich.

    • Netzwerk Internet und Digitalisierung Ostbayern.

    Online 02.05.2022.

    (2022)

    Vortrag
    • Robert Hable

    KI in der Produktion – Methoden, Praxisbeispiele, Strategien.

    Online 09.12.2022.

    (2022)

    Zeitschriftenartikel
    • H. Strobl
    • A. Hermann-Johns
    • J. Loss
    • Robert Hable
    • S. Tittlbach

    A Person-Centered Perspective on Physical Activity-Related Barriers Perceived by Male Fluctuators 50 Plus: A Cross-Sectional Study.

    In: American Journal of Men's Health (vol. 17) , pg. 15579883231193915

    (2023)

    DOI: 10.1177/15579883231193915

    Abstract anzeigen

    Men aged 50 or older (50 plus) represent a hard-to-reach target group for health-enhancing physical activity (PA) interventions. However, a considerable percentage of men 50 plus do not entirely fail to achieve the PA milestones set by the World Health Organization (WHO) guidelines. They show fluctuating PA behavior, influenced by various barriers hindering or preventing regular PA participation. As "one-size-fits-all" behavioral change interventions are only partially effective in specific subgroups, it is essential to tailor PA promotion measures to the particular needs of male fluctuators 50 plus. The standardized questionnaire included validated instruments measuring participants' current stage of behavioral change, their perceived barriers to PA, questions on selected psychosocial correlates of PA, and sociodemographic variables. Out of 1,013 participants, 133 men (13.1%) classified themselves as fluctuators. Using a person-centered approach, we formed groups with similar intra-individual relevant barrier profiles using hierarchical cluster analysis (Ward method) followed by k-means clustering. We identified four clusters. Cluster 1 (n = 31) involves men predominantly perceiving physical constraints. Cluster 2 (n = 33) represents men lacking self-motivation and struggling with their weaker selves. Men in Cluster 3 (n = 51) primarily indicate professional and private obligations that prevent them from being physically active. Finally, men in Cluster 4 (n = 18) miss appropriate sports courses that meet their individual needs. Our findings support identifying individually tailored strategies designed to promote regular PA in male fluctuators 50 plus. Further research is required to determine the effectiveness of this approach in improving adherence to PA guidelines and corresponding health-enhancing effects for men 50 plus.
    Zeitschriftenartikel
    • N. Ramadanov
    • P. Marinova-Kichikova
    • Robert Hable
    • D. Dimitrov
    • R. Becker

    Comparison of Postoperative Serum Biomarkers after Total Hip Arthroplasty through Minimally Invasive Versus Conventional Approaches: A Systematic Review and Meta-Analysis of Randomized Controlled Trials.

    In: Prosthesis (vol. 5) , pg. 694-710

    (2023)

    DOI: 10.3390/prosthesis5030049

    Abstract anzeigen

    Background: An effective way to objectively assess intraoperative tissue damage in total hip arthroplasty (THA) is to determine and compare postoperative serum biomarkers (laboratory parameters) such as creatine kinase (CK), C-reactive protein (CRP), and hemoglobin (Hb). This meta-analysis aims to compare the intraoperative tissue damage in THA through minimally invasive (MI) and conventional approaches (CAs) using postoperative serum biomarkers. Methods: We searched databases for randomized controlled trials (RCTs) comparing MI THA and CA THA. We calculated mean differences (MDs) with 95% confidence intervals (CIs) for continuous outcomes, using the Hartung–Knapp–Sidik–Jonkman method and a common effect/random effects model. Results: A total of 13 RCTs, involving 1186 THA patients, were included in our meta-analysis. In two out of eleven examined outcome parameters, MI THA showed better results than CA THA. In nine out of eleven examined outcome parameters, MI THA showed no significant difference compared to CA THA. MI THA had a 16 mg/L lower CRP value 3 days postoperatively than CA THA (I2 = 66%, p = 0.03, MD = −15.65, 95% CI −30.10 to −1.21). MI THA had a 3 mg/L lower CRP value 4 days postoperatively than CA THA (I2 = 0%, p = 0.98, MD = −3.00, 95% CI −3.27 to −2.74). Conclusions: Overall, there was no significant difference between MI THA and CA THA in terms of postoperative serum biomarkers, with a slight advantage of MI THA in CRP values. These results do not provide sufficient evidence to recommend changing the surgical approach from CA THA to MI THA. Level of evidence I: a systematic review of all relevant randomized controlled trials.
    Zeitschriftenartikel
    • N. Ramadanov
    • P. Marinova-Kichikova
    • Robert Hable
    • D. Dimitrov

    Minimally Invasive versus Conventional Approaches in Total Hip Arthroplasty: A Systematic Review and Meta-Analysis of 47 Randomized Controlled Trials.

    In: Prosthesis (vol. 5) , pg. 962-991

    (2023)

    DOI: 10.3390/prosthesis5030067

    Abstract anzeigen

    Background: Recent meta-analyses have shown indifferent results between minimally invasive (MI) and conventional approach (CA) total hip arthroplasty (THA), not including the superior MI approach SuperPATH. The aim was to compare the surgical, functional and radiological outcomes and postoperative complications of MI THA, including SuperPATH, with CA THA in patients with hip disease or femoral neck fracture. Methods: PubMed, CNKI, The Cochrane Library, clinical trials, CINAHL and Embase were searched for randomized controlled trials (RCTs) comparing MI THA and CA THA up to 31 July 2023. Mean differences (MDs) with 95% confidence intervals (CIs) were calculated for continuous outcomes and odds ratios (ORs) with 95% CIs were calculated for dichotomous outcomes using a common effect/random effects model. The random effects model was used to present the results. Heterogeneity was assessed using the Cochrane Q test and the Higgins I2 test. Results: A total of 47 RCTs with 4086 THAs in 4063 patients were included in our meta-analysis. MI THA showed better results than CA THA in 8 of 18 outcome parameters studied. MI THA showed a higher Harris Hip Score (HHS) than CA THA at 0–1.5, 3, 6 and ≥12 months postoperatively (p < 0.01; p = 0.02; p = 0.01; p = 0.01). MI THA showed an indifferent overall postoperative complication risk compared to CA THA (p = 0.61). Acetabular positioning angles were within the safe zone in all approaches. Conclusions: The results of the meta-analysis suggest that MI THA has several advantages over CA THA in terms of short-term surgical and functional outcomes, with equal postoperative complication rates. We cannot recommend a change in surgical approach based on our results, as the differences between the investigated approaches did not reach minimal clinically important differences. Level of evidence I: a systematic review of all relevant randomized controlled trials.
    Zeitschriftenartikel
    • N. Ramadanov
    • M. Ostojic
    • P. Lazaru
    • K. Liu
    • Robert Hable
    • P. Marinova-Kichikova
    • D. Dimitrov
    • R. Becker

    Risk Factors and Predictors for Functional Outcome and Complication Rate in Total Hip Arthroplasty through Minimally Invasive and Conventional Approaches: A Systematic Review and Meta-Regression Analysis of 41 Randomized Controlled Trials.

    In: Journal of Clinical Medicine (vol. 12) , pg. 5895

    (2023)

    DOI: 10.3390/jcm12185895

    Abstract anzeigen

    Objective: To investigate and identify risk factors and predictors for the difference in functional outcome and complications between total hip arthroplasty (THA) through minimally invasive and conventional approaches, using a meta-regression analysis of randomized controlled trials (RCTs). Methods: A systematic review of the literature up to 31 July 2022 was performed. A meta-regression was conducted based on a random effects meta-analysis using the Hartung–Knapp–Sidik–Jonkman method. Results: A total of 41 RCTs with 3607 patients were found. The following predictors of HHS ≥ 6 months postoperatively were identified: patient age (predictor estimate = 0.14; p < 0.01), avascular necrosis of the femoral head (predictor estimate = −0.03; p = 0.04); incision length (predictor estimate = −0.82; p < 0.01). The following predictors of complication rate were identified: osteoarthritis (predictor estimate = 0.02; p = 0.02); femoral neck fracture (predictor estimate = −0.02; p = 0.02); SuperPATH (predictor estimate = −1.72; (p < 0.01). Conclusions: Patient age, avascular necrosis of the femoral head, and incision length were identified as predictors of the effect size of the HHS ≥ 6 months postoperatively; and osteoarthritis, femoral neck fracture, and SuperPATH as predictors of the effect size of the complication rate. Based on these findings, we recommend that more frequent use of minimally invasive THA in elderly patients should be considered. Level of evidence I: a systematic review of all relevant randomized controlled trials. Registered in PROSPERO on 10 August 2022 (CRD42022350287).
    Vortrag
    • Robert Hable

    Fragebögen erstellen und auswerten - (k)eine Wissenschaft für sich.

    • Netzwerk Internet und Digitalisierung Ostbayern.

    Online 13.02.2023.

    (2023)

    Zeitschriftenartikel
    • N. Ramadanov
    • M. Salzmann
    • M. Voss
    • Robert Hable
    • H. Hakam
    • R. Prill
    • D. Dimitrov
    • R. Becker

    The influence of operation time for hip hemiarthroplasty on complication rates and mortality in patients with femoral neck fracture: a retrospective data analysis.

    In: Journal of Orthopaedic Surgery and Research (vol. 19) , pg. 311

    (2024)

    DOI: 10.1186/s13018-024-04797-7

    Abstract anzeigen

    BACKGROUND The aim of the present study was to investigate the influence of various factors, in particular operation time, on mortality and complication rates in patients with femoral neck fractures who have undergone hip hemiarthroplasty (HHA) and to determine a cut-off value above which mortality and complication rates increase significantly. METHODS Cases of patients with femoral neck fracture treated with HHA between 1 January 2017 and 31 December 2023 were screened for eligibility. Multiple logistic regressions were calculated to determine which factors (patient age, experience of surgeon, patient sex, ASA score, time to surgery, operation time) influenced the incidence of complications and mortality. The exact cut-off value for complications and mortality was determined using the Youden index of the ROC curve (sensitivity vs. specificity) of logistic regression. RESULTS A total of 552 patients were considered eligible for this study. During the 90-day follow-up period after HHA, 50 deaths and 34 complications were recorded, giving a mortality rate of 9.1%, and a complication rate of 6.2%. Of the 34 complications recorded, 32.3% were infections, 14.7% dislocations, 20.7% trochanteric avulsions, 11.8% periprosthetic fractures, 11.8% nerve injuries, and 8.8% deep vein thrombosis. The odds ratio (OR) of a patient experiencing a complication is 2.2% higher for every minute increase in operation time (Exponential Beta - 1 = 0.022; p = 0.0363). The OR of a patient dying is 8.8% higher for each year increase in age (Exponential Beta - 1 = 0.088; p = 0.0007). When surgery was performed by a certified orthopaedic surgeon the mortality rate lowered by 61.5% in comparison to the surgery performed by a trainee (1 - Exponential Beta = 0.594; p = 0.0120). Male patients have a 168.7% higher OR for mortality than female patients (Exponential Beta - 1 = 1.687; p = 0.0017). Patients with an operation time of ≥ 86 min. have a 111.8% higher OR for mortality than patients with an operation time of < 86 min. (Exponential Beta - 1 = 1.118). CONCLUSION This retrospective data analysis found that the risk of a patient experiencing a complication was 2.2% higher for every minute increase in operation time. Patients with an operation time above the cut-off of 86 min had a 111.8% higher risk of mortality than those with an operation time below the cut-off. Other influencing factors that operators should be aware of include patient age, male sex, and operator experience.
    Zeitschriftenartikel
    • N. Ramadanov
    • M. Salzmann
    • M. Voss
    • Robert Hable
    • H. Hakam
    • R. Prill
    • D. Dimitrov
    • R. Becker

    Response to the letter to the editor by Prof. Raju Vaishya and Dr. Abhishek Vaish regarding our recent publication in the Journal of Orthopaedic Surgery and Research: "The influence of operation time for hip hemiarthroplasty in patients with femoral neck fracture: a retrospective data analysis".

    In: Journal of Orthopaedic Surgery and Research (vol. 19) , pg. 530

    (2024)

    DOI: 10.1186/s13018-024-05016-z

    Zeitschriftenartikel
    • N. Ramadanov
    • M. Voss
    • Robert Hable
    • R. Prill
    • H. Hakam
    • M. Salzmann
    • D. Dimitrov
    • R. Becker

    Patient-related Predictors for the Functional Outcome of SuperPATH Hemiarthroplasty versus Conventional Approach Hemiarthroplasty: A Systematic Review and Meta-regression Analysis of Randomized Controlled Trials.

    In: Orthopaedic Surgery (vol. 16) , pg. 791-801

    (2024)

    DOI: 10.1111/os.14006

    Abstract anzeigen

    Specialist literature lacks evidence that explores associations between patient characteristics and the beneficial treatment effect of SuperPATH hemiarthroplasty (HA) compared with conventional approach (CA) HA. To investigate and identify patient-related predictors of the effect size of the short-term functional outcome of SuperPATH HA and CA HA by performing a systematic review and meta-regression analysis of randomized controlled trials (RCTs). A systematic search of literature was performed in PubMed, CNKI, CENTRAL of The Cochrane Library, Clinical trials, and Google Scholar until August 25, 2023. For the continuous outcome parameter Harris hip score (HHS) ≤1 week and 3 months postoperatively, mean differences (MDs) with 95% confidence intervals (CIs) were calculated. A meta-regression analysis was based on random-effects meta-analysis using the Hartung-Knapp-Sidik-Jonkman method for continuous covariates. A total of five RCTs with 404 patients were found. The following predictors of HHS ≤1 week postoperatively were identified: patient age (predictor estimate = 1.29; p < 0.01), patient age groups (predictor estimate = 14.07; p < 0.01), time to mobilization (predictor estimate = 5.51; p < 0.01). The following predictors of HHS 3 months postoperatively were identified: incision length (predictor estimate = -2.12; p < 0.01); intraoperative blood loss (predictor estimate = 0.02; p < 0.01). Patient age, time to mobilization, incision length, and intraoperative blood loss were identified as predictors of the effect size of early postoperative functional outcome as measured by HHS. Elderly patients, particularly those over 70 years of age, appear to benefit from SuperPATH HA. Based on these findings, and taking into account our limitations, we recommend that the use of minimally invasive SuperPATH HA in elderly patients should be more widely considered and not limited to elective THA patients.
    Vortrag
    • Robert Hable

    Fragebögen erstellen und auswerten - (k)eine Wissenschaft für sich.

    • Netzwerk Internet und Digitalisierung Ostbayern.

    Online 22.01.2024.

    (2024)

    Zeitschriftenartikel
    • N. Ramadanov
    • M. Voss
    • Robert Hable
    • H. Hassan Tarek
    • R. Prill
    • M. Salzmann
    • D. Dimitrov
    • R. Becker

    Postoperative Harris Hip Score Versus Harris Hip Score Difference in Hip Replacement: What to Report?.

    In: Orthopaedic Surgery (vol. 17) , pg. 3-21

    (2025)

    DOI: 10.1111/os.14272

    Abstract anzeigen

    BACKGROUND Reliable scientific information is crucial for assessing hip function and evaluating the success of hip surgery. The Harris Hip Score (HHS) is the most widely used tool for measuring hip function and, in particular, the outcomes of hip surgery. The aim of this study was to conduct a systematic review of the literature to identify randomized controlled trials (RCTs) that reported the HHS for hip replacement treatment groups and to test whether there was a substantial difference between reporting only the postoperative HHS or the HHS difference (HHSdiff). METHODS PubMed, CNKI, and Epistemonikos were searched until March 1, 2024. The risk of bias, level of evidence, and publication bias were assessed. As HHS is a continuous outcome, mean difference (MD) with 95% confidence intervals (CIs) was calculated using the Hartung-Knapp-Sidik-Jonkman method and a common-effect/random-effects model. The same approach was used for both postoperative HHS and HHSdiff. The effect of the two treatment groups studied (minimally invasive vs. conventional approach) on postoperative HHS was then compared with the effect of the two groups studied on the difference in HHS. RESULTS A total of 41 RCTs, involving 3572 patients, with a low to high risk of bias and a low to moderate publication bias were included. The measured outcome parameters showed a low to moderate level of evidence. There was no relevant difference in the reporting of HHS only postoperatively or HHSdiff when comparing two hip replacement treatment groups in RCTs, measured at 0-0.5, 3, 6, and 12 months postoperatively. CONCLUSION The present study showed that there is no relevant difference between reporting of the HHS only postoperatively or HHSdiff when comparing two hip replacement treatment groups in RCTs. Both methods of HHS reporting produced comparable results in an identical cohort of 3765 patients undergoing hip replacement surgery.
    Zeitschriftenartikel
    • M. Salzmann
    • H. Hassan Tarek
    • R. Prill
    • R. Becker
    • A. Schreyer
    • Robert Hable
    • M. Ostojic
    • N. Ramadanov

    Artificial intelligence-based assessment of leg axis parameters shows excellent agreement with human raters: A systematic review and meta-analysis.

    In: Knee Surgery, Sports Traumatology, Arthroscopy : official journal of the ESSKA (vol. 33) , pg. 177-190

    (2025)

    DOI: 10.1002/ksa.12362

    Abstract anzeigen

    PURPOSE The aim of this study was to conduct a systematic review and meta-analysis on the reliability and applicability of artificial intelligence (AI)-based analysis of leg axis parameters. We hypothesized that AI-based leg axis measurements would be less time-consuming and as accurate as those performed by human raters. METHODS The study protocol was registered with the International Prospective Register of Systematic Reviews (PROSPERO). PubMed, Epistemonikos, and Web of Science were searched up to 24 February 2024, using a BOOLEAN search strategy. Titles and abstracts of identified records were screened through a stepwise process. Data extraction and quality assessment of the included papers were followed by a frequentist meta-analysis employing a common effect/random effects model with inverse variance and the Sidik-Jonkman heterogeneity estimator. RESULTS A total of 13 studies encompassing 3192 patients were included in this meta-analysis. All studies compared AI-based leg axis measurements on long-leg radiographs (LLR) with those performed by human raters. The parameters hip knee ankle angle (HKA), mechanical lateral distal femoral angle (mLDFA), mechanical medial proximal tibial angle (mMPTA), and joint-line convergence angle (JLCA) showed excellent agreement between AI and human raters. The AI system was approximately 3 min faster in reading standing long-leg anteroposterior radiographs (LLRs) compared with human raters. CONCLUSION AI-based assessment of leg axis parameters is an efficient, accurate, and time-saving procedure. The quality of AI-based assessment of the investigated parameters does not appear to be affected by the presence of implants or pathological conditions. LEVEL OF EVIDENCE Level I.