Publications associées à Privacy-Preserving Exploration of Genetic Cohorts with i2b2 At Lausanne University Hospital

Classification of patients with cardiac amyloidosis using machine learning models on Italian electronic clinical health records

Amyloidosis refers to a range of medical conditions in which misshapen proteins accumulate in various organs and tissues, forming insoluble fibrils. Cardiac amyloidosis is frequently linked to the buildup of misfolded transthyretin (TTR) or immunoglobulin ...

IEEE2023

Controlled physics-informed data generation for deep learning-based remaining useful life prediction under unseen operation conditions

Olga Fink, Jian Zhou

Limited availability of representative time-to-failure (TTF) trajectories either limits the performance of deep learning (DL)-based approaches on remaining useful life (RUL) prediction in practice or even precludes their application. Generating synthetic d ...

2023

Generating Controlled Physics-Informed Time-to-failure Trajectories for Prognostics in Unseen Operational Conditions

Olga Fink, Jian Zhou

Limited availability of representative time-to-failure (TTF) trajectories either limits the performance of deep learning (DL)-based approaches on remaining useful life (RUL) prediction in practice or even precludes their application. Generating synthetic d ...

Research Publishing2023

Modeling tumor size dynamics based on real-world electronic health records and image data in advanced melanoma patients receiving immunotherapy

Olivier Michielin, Federico Amato, Monia Guidi, Nadia Terranova, Daniel Abler, Alexandre Wicky

The development of immune checkpoint inhibitors (ICIs) has revolutionized cancer therapy but only a fraction of patients benefits from this therapy. Model-informed drug development can be used to assess prognostic and predictive clinical factors or biomark ...

2023

Health data privacy through homomorphic encryption and distributed ledger computing: an ethical-legal qualitative expert assessment study

Marcello Ienca

Background: Increasingly, hospitals and research institutes are developing technical solutions for sharing patient data in a privacy preserving manner. Two of these technical solutions are homomorphic encryption and distributed ledger technology. Homomorph ...

BMC2022

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

Jean-Pierre Hubaux, Bryan Alexander Ford, Olivier Michielin, Juan Ramón Troncoso-Pastoriza, Jean Louis Raisaro, Joao André Gomes de Sá e Sousa, Mickaël Misbach

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-preservin ...

2019

Protecting Privacy and Security of Genomic Data in i2b2 with Homomorphic Encryption and Differential Privacy

Jean-Pierre Hubaux, Jean Louis Raisaro, Gwangbae Choi, Nathalie Jacquemont, Nicolas Rosat

Re-use of patients’ health records can provide tremendous benefits for clinical research. Yet, when researchers need to access sensitive/identifying data, such as genomic data, in order to compile cohorts of well-characterized patients for specific studies ...

IEEE2018

Privacy - Preserving Data Exchange and Aggregation in Healthcare

Alevtina Dubovitskaya

Medical data are often scattered among multiple clinics, hospitals, insurance companies, pharmacies, and research institutions that store and process personal healthcare information. The use of information and communication technologies for health (eHealth ...

EPFL2018

MedCo: Enabling Privacy-Conscious Exploration of Distributed Clinical and Genomic Data

Jean-Pierre Hubaux, Jean Louis Raisaro, Bryan Alexander Ford, Olivier Michielin, Juan Ramón Troncoso-Pastoriza, Joao André Gomes de Sá e Sousa, Mickaël Misbach

Being able to share large amounts of sensitive clinical and genomic data across several institutions is crucial for precision medicine to scale up. Unfor- tunately, existing solutions only partially address this challenge and are still unable to provide th ...

2017

Digital Pharmacovigilance and Disease Surveillance: Combining Traditional and Big-Data Systems for Better Public Health

Marcel Salathé

The digital revolution has contributed to very large data sets (ie, big data) relevant for public health. The two major data sources are electronic health records from traditional health systems and patient-generated data. As the two data sources have comp ...

Oxford University Press (OUP)2016