Precision medicine seeks to maximize the quality of health care by individualizing the health-
care process to the uniquely evolving health status of each patient. This endeavor spans a …

Résumé En France, le législateur a souhaité en 1999 que les régimes d'Assurance Maladie
développent un système national d'information interrégimes de l'Assurance Maladie …

Knowledge gained from observational cohort studies has dramatically advanced the
prevention and treatment of diseases. Many of these cohorts, however, are small, lack …

Mental illnesses, such as depression, are highly prevalent and have been shown to impact
an individual's physical health. Recently, artificial intelligence (AI) methods have been …

Modern electronic health records (EHRs) provide data to answer clinically meaningful
questions. The growing data in EHRs makes healthcare ripe for the use of machine learning …

ACE (angiotensin-converting enzyme) inhibitors and angiotensin receptor blockers (ARBs)
are equally guideline-recommended first-line treatments for hypertension, yet few head-to …

There is increasing awareness that the methodology and findings of research should be
transparent. This includes studies using artificial intelligence to develop predictive …

Artificial intelligence (AI) supported clinical decision support (CDS) technologies can parse
vast quantities of patient data into meaningful insights for healthcare providers. Much work is …

Precision public health is an emerging practice to more granularly predict and understand
public health risks and customize treatments for more specific and homogeneous …

Objective To develop a conceptual prediction model framework containing standardized
steps and describe the corresponding open-source software developed to consistently …