Objective To assess the methodological quality of studies on prediction models developed
using machine learning techniques across all medical specialties. Design Systematic …

Recent years have seen the rapid proliferation of clinical prediction models aiming to
support risk stratification and individualized care within psychiatry. Despite growing interest …

The increase of mental health problems and the need for effective medical health care have
led to an investigation of machine learning that can be applied in mental health problems …

Annually, approximately 30 million patients are discharged from the emergency department
(ED) after a traumatic event. These patients are at substantial psychiatric risk, with …

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

Abstract The advent of Artificial Intelligence (AI) has resulted in development of novel
applications in a multitude of fields, such as in Medicine, to aid medical professionals in …

Establishing the diagnosis of trauma-related disorders such as Acute Stress Disorder (ASD)
and Posttraumatic Stress Disorder (PTSD) have always been a challenge in clinical practice …

Importance A substantial proportion of the 40 million people in the US who present to
emergency departments (EDs) each year after traumatic events develop posttraumatic stress …

Stress is one type of epidemic of current world. It generates many diseases and is a big
source of human suicide. The main aim of this paper is to determine the work of this study …

The necessary requirement of a traumatic event preceding the development of Posttraumatic
Stress Disorder, theoretically allows for administering preventive and early interventions in …