Despite therapeutic advances, lung cancer remains the first cause of death from cancer. The main objective of this study was to identify risk factors associated with death within 3-months of the first hospitalization for lung cancer in France.
This in-depth analysis determined significantly distinct typologies of inpatients, which facilitated definition of medical protocols to deliver the most appropriate cares for each profile.
Evolution of hospitalized patient characteristics through the first three COVID-19 waves in Paris area using machine learning analysis
Evaluate the ability of an AI model (Deep Learning) to distinguish different eye pathologies to accelerate diagnosis
Obesity is strongly associated with many types of cancer. The goal of this study is to determine if bariatric surgery is associated with a lower risk of cancer.
Collaboration with CHI Créteil to study the impact of the establishment of a reference center for rare lung diseases on the care pathway of patients
Lyme disease is the most common vector-borne disease in France – its diagnosis sometimes leads to medical wanderings for patients and a significant cost for the healthcare system.
As machine learning (ML) is now widely applied in many fields, understanding what happens inside the black box is becoming a growing demand, especially by non-experts of these models.
This study analyzes trends in metabolic bariatric surgery among adolescents in France on the basis of national data over an 11-year period
In particular, this study reveals many similarities in the pattern of publications and procedures in bariatric surgery
To cope with the burden of disease, hospital staff were reassigned and elective surgery was significantly delayed. Various countries implemented national containment […].
