L'intelligence hybride pour prédire l'évolution des maladies chroniques: Hybrid intelligence to predict chronic disease progression.

In personalized medicine, care individualization is a key challenge to provide a more adapted and personalized clinical decision for each patient. The access to large amounts of medical data with the available computational power as well as the evolution of Artificial Intelligence (AI) algorithms allow to overcome this challenge. However, the application of AI algorithms must enable efficient and accurate communication with physicians. The complementarity between human and artificial intelligence holds the most promise for a safe and innovative medical future. We propose a new personalized medicine approach to improve the results of machine learning algorithms and overcome some barriers to the adoption of AI in medical practice. The proposed approach is based on human-machine interaction to create predictive models of chronic disease progression, especially for multiple sclerosis (MS).