Augmented brain monitoring solution for general anesthesia to reduce the risk of postoperative complications
Description
Names of partners involved
AP-HP, Inria (équipe-projet MIND, ex PARIETAL)
PREDICT
Invidualized prediction of persIstance of biological treatments in psoriasis patients
Underway
01/11/2024
-
31/10/2025
Main objectives
The aim of the present project is therefore to develop a statistical learning model that will predict the persistence of each biological treatment for each psoriasis patient, based on his or her characteristics and course of care.
Challenge
Psoriasis is a chronic inflammatory dermatosis for which numerous biological treatments are available to treat moderate to severe forms. The persistence of these treatments (i.e. the duration of treatment from initiation to discontinuation) decreases rapidly over time, due to secondary inefficacy or the occurrence of adverse events. In order to guide the choice between therapeutic options, an individualized prediction of persistence is required
Methodology/Technology used
Supervised statistical ensemble learning methods adapted to survival data.
Publications
Contacts
Léa Hoisnard () & Judith Abecassis ()
Members
AP-HP, Inria
Other projects
Description
Innovation Chair “Augmented Operating Room”
Names of partners involved
AP-HP, Inria, Institut Mines-Télécom, Université de Paris-Saclay, Chaire Humanité et Santé du CNAM
