Artificial intelligence (AI) is increasingly employed in health care fields such as oncology,
radiology, and dermatology. However, the use of AI in mental health care and …

Importance Suicide prediction models have the potential to improve the identification of
patients at heightened suicide risk by using predictive algorithms on large-scale data …

Background As more and more researchers are turning to big data for new opportunities of
biomedical discoveries, machine learning models, as the backbone of big data analysis, are …

Suicide is a leading cause of death that defies prediction and challenges prevention efforts
worldwide. Artificial intelligence (AI) and machine learning (ML) have emerged as a means …

Objective: Electronic health records (EHRs) are an increasingly common data source for
clinical risk prediction, presenting both unique analytic opportunities and challenges. We …

Objective: The purpose of this article was to determine whether longitudinal historical data,
commonly available in electronic health record (EHR) systems, can be used to predict …

Aims frailty is proposed as a summative measure of health status and marker of individual
vulnerability. We aimed to investigate the discriminative capacity of a frailty index (FI) …

Introduction Most individuals make healthcare visits before suicide, but many do not have a
diagnosed mental health condition. This study seeks to investigate suicide risk among …

Hercules Dalianis Secondary Use of Electronic Patient Records Page 1 Hercules Dalianis
Clinical Text Mining Secondary Use of Electronic Patient Records Page 2 Clinical Text …

Background The impact of precision psychiatry for clinical practice has not been
systematically appraised. This study aims to provide a comprehensive review of validated …