dsMTL: a computational framework for privacy-preserving, distributed multi-task machine learning.

Journal: Bioinformatics (Oxford, England)
Published Date: Oct 31, 2022

Abstract

MOTIVATION: In multi-cohort machine learning studies, it is critical to differentiate between effects that are reproducible across cohorts and those that are cohort-specific. Multi-task learning (MTL) is a machine learning approach that facilitates this differentiation through the simultaneous learning of prediction tasks across cohorts. Since multi-cohort data can often not be combined into a single storage solution, there would be the substantial utility of an MTL application for geographically distributed data sources.

Authors

  • Han Cao
    Department of Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, 68159 Mannheim, Germany. han.cao@zi-mannheim.de.
  • Youcheng Zhang
    Health Data Science Unit, Medical Faculty Heidelberg & BioQuant, Heidelberg 69120, Germany.
  • Jan Baumbach
    TUM School of Life Sciences Weihenstephan, Technical University of Munich, Freising, Germany.
  • Paul R Burton
    Population Health Sciences Institute, Newcastle University, Newcastle upon Tyne NE2 4AX, UK.
  • Dominic Dwyer
    Department of Psychiatry and Psychotherapy, Klinikum der Universität München, Ludwig-Maximilians-Universität, Munich.
  • Nikolaos Koutsouleris
    Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, United Kingdom.
  • Julian Matschinske
    Chair of Experimental Bioinformatics, TUM School of Life Sciences, Technical University of Munich, Freising, Germany.
  • Yannick Marcon
    Epigeny, St Ouen, France.
  • Sivanesan Rajan
    Department of Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim 68158, Germany.
  • Thilo Rieg
    Machine Learning Research Group, Aalen University, Aalen, Germany.
  • Patricia Ryser-Welch
    Population Health Sciences Institute, Newcastle University, Newcastle upon Tyne NE2 4AX, UK.
  • Julian Späth
    Chair of Computational Systems Biology, University of Hamburg, Hamburg 22607, Germany.
  • Carl Herrmann
    IPMB, Universität Heidelberg and Department of Theoretical Bioinformatics, DKFZ, Heidelberg 69120, Germany.
  • Emanuel Schwarz
    Department of Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, 68159 Mannheim, Germany. emanuel.schwarz@zi-mannheim.de.

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