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Webinar QuanTIM

Event date
to 12:00, (Paris, Europe)
Event location
En ligne
Professeur Roch GIORGI - Equipe QuanTIM-SESSTIM
Speaker
Richard RILEY
Institute of Applied Health Research, University of Birmingham, UK
Description

Clinical prediction models estimate an individual’s risk of a particular health outcome. In this talk, I suggest that prediction model research has become the academic’s playground, and that machine learning and AI have only exacerbated this problem. I highlight common pitfalls, including model instability and poor calibration, and propose some solutions moving forwards. The talk is aimed at a broad audience.

Keywords: Clinical prediction models, machine learning, AI, predictive algorithms, stability