Establishing the means to improve performance in healthy, clinical, and military populations
has long been a focus of study in the psychological and brain sciences. However, a major …

Importance Neuroimaging-based artificial intelligence (AI) diagnostic models have
proliferated in psychiatry. However, their clinical applicability and reporting quality (ie …

Background Rapid technological advancements have laid the foundations for the use of
artificial intelligence in medicine. The promise of machine learning (ML) lies in its potential …

The TRIPOD (Transparent Reporting of a multivariable prediction model for Individual
Prognosis Or Diagnosis) statement was published in 2015 to provide the minimum reporting …

Background Advancements in artificial intelligence (AI) have led to the creation of large
language models (LLMs), such as Chat Generative Pretrained Transformer (ChatGPT) and …

The aim of this study is to identify the best practices and future research directions for driver
lane-change intention (DLCI) prediction using eye-tracking technologies based on a …

Background The surgical management of complications after total hip arthroplasty (THA)
necessitates accurate identification of the femoral implant manufacturer and model …

Background: Limited health literacy has been associated with adverse health outcomes.
Undergoing orthopedic surgery often requires patients to make complex decisions and …

Background Accurate diagnostic and prognostic predictions of venous thromboembolism
(VTE) are crucial for VTE management. Artificial intelligence (AI) enables autonomous …

Objectives To (1) explore trends of risk of bias (ROB) in prediction research over time
following key methodological publications, using the Prediction model Risk Of Bias …