Literature DB >> 30010584

MedCo: Enabling Secure and Privacy-Preserving Exploration of Distributed Clinical and Genomic Data.

Jean Louis Raisaro, Juan Ramon Troncoso-Pastoriza, Mickael Misbach, Joao Sa Sousa, Sylvain Pradervand, Edoardo Missiaglia, Olivier Michielin, Bryan Ford, Jean-Pierre Hubaux.   

Abstract

The increasing number of health-data breaches is creating a complicated environment for medical-data sharing and, consequently, for medical progress. Therefore, the development of new solutions that can reassure clinical sites by enabling privacy-preserving sharing of sensitive medical data in compliance with stringent regulations (e.g., HIPAA, GDPR) is now more urgent than ever. In this work, we introduce MedCo, the first operational system that enables a group of clinical sites to federate and collectively protect their data in order to share them with external investigators without worrying about security and privacy concerns. MedCo uses (a) collective homomorphic encryption to provide trust decentralization and end-to-end confidentiality protection, and (b) obfuscation techniques to achieve formal notions of privacy, such as differential privacy. A critical feature of MedCo is that it is fully integrated within the i2b2 (Informatics for Integrating Biology and the Bedside) framework, currently used in more than 300 hospitals worldwide. Therefore, it is easily adoptable by clinical sites. We demonstrate MedCo's practicality by testing it on data from The Cancer Genome Atlas in a simulated network of three institutions. Its performance is comparable to the ones of SHRINE (networked i2b2), which, in contrast, does not provide any data protection guarantee.

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Year:  2018        PMID: 30010584     DOI: 10.1109/TCBB.2018.2854776

Source DB:  PubMed          Journal:  IEEE/ACM Trans Comput Biol Bioinform        ISSN: 1545-5963            Impact factor:   3.710


  9 in total

1.  Fold-stratified cross-validation for unbiased and privacy-preserving federated learning.

Authors:  Romain Bey; Romain Goussault; François Grolleau; Mehdi Benchoufi; Raphaël Porcher
Journal:  J Am Med Inform Assoc       Date:  2020-08-01       Impact factor: 4.497

2.  Privacy-preserving federated neural network learning for disease-associated cell classification.

Authors:  Sinem Sav; Jean-Philippe Bossuat; Juan R Troncoso-Pastoriza; Manfred Claassen; Jean-Pierre Hubaux
Journal:  Patterns (N Y)       Date:  2022-04-18

3.  Data Science in Environmental Health Research.

Authors:  Christine Choirat; Danielle Braun; Marianthi-Anna Kioumourtzoglou
Journal:  Curr Epidemiol Rep       Date:  2019-07-15

Review 4.  Differential privacy in health research: A scoping review.

Authors:  Joseph Ficek; Wei Wang; Henian Chen; Getachew Dagne; Ellen Daley
Journal:  J Am Med Inform Assoc       Date:  2021-09-18       Impact factor: 7.942

Review 5.  Digital microbiology.

Authors:  A Egli; J Schrenzel; G Greub
Journal:  Clin Microbiol Infect       Date:  2020-06-27       Impact factor: 8.067

Review 6.  Big Data in Laboratory Medicine-FAIR Quality for AI?

Authors:  Tobias Ueli Blatter; Harald Witte; Christos Theodoros Nakas; Alexander Benedikt Leichtle
Journal:  Diagnostics (Basel)       Date:  2022-08-09

7.  Privacy-Preserving Artificial Intelligence Techniques in Biomedicine.

Authors:  Reihaneh Torkzadehmahani; Reza Nasirigerdeh; David B Blumenthal; Tim Kacprowski; Markus List; Julian Matschinske; Julian Spaeth; Nina Kerstin Wenke; Jan Baumbach
Journal:  Methods Inf Med       Date:  2022-01-21       Impact factor: 1.800

8.  Decentralized genomics audit logging via permissioned blockchain ledgering.

Authors:  Nicholas D Pattengale; Corey M Hudson
Journal:  BMC Med Genomics       Date:  2020-07-21       Impact factor: 3.063

9.  Revolutionizing Medical Data Sharing Using Advanced Privacy-Enhancing Technologies: Technical, Legal, and Ethical Synthesis.

Authors:  James Scheibner; Jean Louis Raisaro; Juan Ramón Troncoso-Pastoriza; Marcello Ienca; Jacques Fellay; Effy Vayena; Jean-Pierre Hubaux
Journal:  J Med Internet Res       Date:  2021-02-25       Impact factor: 5.428

  9 in total

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