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Detecting the impact of subject characteristics on machine learning-based diagnostic applications., , , , , , , , , and . npj Digit. Medicine, (2019)Indicators of retention in remote digital health studies: A cross-study evaluation of 100, 000 participants., , , , , , , , , and 4 other author(s). CoRR, (2019)Stable predictions for health related anticausal prediction tasks affected by selection biases: the need to deconfound the test set features., , , and . CoRR, (2020)Thinking outside the box: Statistical inference based on Kullback-Leibler empirical projections, , , and . Statistics & Probability Letters, 77 (12): 1201--1213 (Jul 1, 2007)A novel estimator for the two-way partial AUC., , , and . BMC Medical Informatics Decis. Mak., 24 (1): 57 (December 2024)A Permutation Approach to Assess Confounding in Machine Learning Applications for Digital Health., , , , , , and . KDD, page 54-64. ACM, (2019)Identifying robust clusters and multi-community nodes by combining top-down and bottom-up approaches to clustering., , , , , , , , , and 2 other author(s). CoRR, (2015)Mindboggling morphometry of human brains, , , , , , , , , and 1 other author(s). PLOS Computational Biology, 13 (2): e1005350+ (Feb 23, 2017)Remote Assessment, in Real-World Setting, of Tremor Severity in Parkinson's Disease Patients Using Smartphone Inertial Sensors., , , , , , and . UbiComp/ISWC Adjunct, page 215-218. ACM, (2018)Causality-Aware Predictions in Static Anticausal Machine Learning Tasks.. IEEE Trans. Neural Networks Learn. Syst., 35 (4): 5039-5053 (April 2024)