Mission

Accelerate research and innovation in digital health by bringing together researchers in digital sciences and healthcare professionals

INRIA-0124-087-v4

© Inria / Photo Kaksonen

Our strategic objectives

picoHP1

Accelerate medical
research based on
health data.

picoHP2

Develop algorithms
for clinical practice.

picoHP3

Stimulate the transfer
of digital health
innovations to the
economic world.

News

The contribution of digital technology to healthcare : Presentation by the Bernoulli Lab at the #aiforhealth conference on July 13th, 2021, co-organized by AI for Health, the French National Assembly and the Presidency of the French National Assembly.

Digital sciences in the broadest sense can benefit the medical community

Dominique Chapelle

Scientific Head of the Daniel Bernoulli Laboratory

We are convinced that the Bernoulli Lab will allow AP-HP professionals to become more proficient in digital sciences, and likewise for Inria researchers in medical sciences

Dominique Chapelle

Scientific Director of the Daniel Bernoulli Laboratory

The Bernoulli Lab, an agile structure shared by AP-HP and Inria, aims to expand the collaboration between the two institutions to develop innovative technologies and tools to improve patient care and the practice of professionals in healthcare institutions

Laure Maillant

Head of the innovation and data unit at the
the AP-HP's IT department

Spotlight

AI-RACLES Chair

Description

Artificial intelligence for the evaluation of profiles, trajectories and management of vulnerability in health: COVID-19, frailty of the elderly and cancer

Names of partners involved
AP-HP, Inria, CentraleSupélec

#ApprentissageSupervisé, #ArtificialIntelligence, #Cancer, #CarePathway, #Clustering, #ComplexData, #DataFusion, #DeepLearning, #Fragilité, #Fragility, #ParcoursDesoins, #Phénotypage, #Phenotyping, #SupervisedLearning,

COVIPREDS

Description

US Caractérisation et prédiction de la survenue de formes graves ou létales du COVID-19 à partir des données issues de l’EDS de l’AP-HP

Names of partners involved
AP-HP, Inria & Centrale Supélec

DEEP PATIENT

Description

Learning a deep representation of patient records for event prediction and patient segmentation

Names of partners involved
AP-HP, Inria

#DeepLearning, #DeepPatient,

Founding institutions

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