Distributed Learning to Protect Privacy in Multi-centric Clinical Studies

Andrea Damiani, Mauro Vallati, Roberto Gatta, Nicola Dinapoli, Arthur Jochems, Timo Deist, Johan van Soest, Andre Dekker, Vincenzo Valentini

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

17 Citations (Scopus)


Research in medicine has to deal with the growing amount of data about patients which are made available by modern technologies. All these data might be used to support statistical studies, and for identifying causal relations. To use these data which are spread across hospitals efficient merging techniques, as well as policies to deal with this sensitive information, are strongly needed. In this paper we introduce and empirically test a distributed learning approach, to train Support Vector Machines (SVM), that allows to overcome problems related to privacy and data being spread around. The introduced technique allows to train algorithms without sharing any patients-related information, ensuring privacy and avoids the development of merging tools. We tested this approach on a large dataset and we described results, in terms of convergence and performance; we also provide considerations about the features of an IT architecture designed to support distributed learning computations.
Original languageEnglish
Title of host publicationArtificial Intelligence in Medicine
Subtitle of host publication15th Conference on Artificial Intelligence in Medicine, AIME 2015, Pavia, Italy, June 17-20, 2015. Proceedings
EditorsJohn H. Holmes, Riccardo Bellazzi, Lucia Sacchi, Niels Peek
PublisherSpringer, Cham
Number of pages11
ISBN (Electronic)9783319195513
ISBN (Print)9783319195506
Publication statusPublished - 2015
Event15th Conference on Artificial Intelligence in Medicine - Pavia, Italy
Duration: 17 Jun 201520 Jun 2015
Conference number: 15
http://aime15.aimedicine.info/ (Link to Conference Website)

Publication series

NameLecture Notes in Computer Science
PublisherSpringer International
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference15th Conference on Artificial Intelligence in Medicine
Abbreviated titleAIME 2015
Internet address


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