Background Machine learning systems are part of the field of artificial intelligence that
automatically learn models from data to make better decisions. Natural language processing …

Mental health researchers and clinicians have long sought answers to the question “What
works for whom?” The goal of precision medicine is to provide evidence-based answers to …

Background The potential of artificial intelligence (AI)–based large language models, such
as ChatGPT, has gained significant attention in the medical field. This enthusiasm is driven …

Synapse density is reduced in postmortem cortical tissue from schizophrenia patients, which
is suggestive of increased synapse elimination. Using a reprogrammed in vitro model of …

Generalized anxiety disorder (GAD) and major depressive disorder (MDD) are highly
prevalent and impairing problems, but frequently go undetected, leading to substantial …

Purpose The South London and Maudsley National Health Service (NHS) Foundation Trust
Biomedical Research Centre (SLaM BRC) Case Register and its Clinical Record Interactive …

Clinical data describing the phenotypes and treatment of patients represents an underused
data source that has much greater research potential than is currently realized. Mining of …

Objective Natural language processing (NLP) combined with machine learning (ML)
techniques are increasingly used to process unstructured/free-text patient-reported outcome …

In secondary analysis of electronic health records, a crucial task consists in correctly
identifying the patient cohort under investigation. In many cases, the most valuable and …

Objective: Individuals at high risk for schizophrenia may benefit from early intervention, but
few validated risk predictors are available. Genetic profiling is one approach to risk …