Introduction Students enrolling in higher education often adopt lifestyles linked to worse mental health, potentially contributing to the peak age onset of mental health problems in early adulthood.

Objective: To understand patient portal engagement stratified by patient characteristics among adults 50 years and older with at least 1 common chronic medical condition using electronic health ...

Abstract: Compared with common 3-D measurements technologies, indirect time-of-flight (i-TOF) systems offers significant advantages in volume, cost, power consumption, accuracy, range, and angular ...

Two trained coders coded the study characteristics independently. The effect sizes were calculated using the correlation coefficient as a standardized measure of the relationship between electronic ...

Background Medical specialists are integral to the medical workforce and play a pivotal role in referral systems. However, in ...

Background The relationship of social determinants of health (SDOH), environmental exposures and medical history to lung function trajectories is underexplored. A better understanding of these ...

Introduction Virtual reality-based telerehabilitation (VR-TR) combines gamified exercises with remote supervision for people with Parkinson’s disease (PD). Its effectiveness and safety in PD remain ...

Background On 14 August 2024, the WHO redesignated Monkeypox (mpox) as a Public Health Emergency of International Concern.

Abstract: In this paper, we analyze the effects of random sampling on adaptive diffusion networks. These networks consist in a collection of nodes that can measure and process data, and that can ...

Randomized controlled trials (RCTs) are considered the gold standard for evaluating surgical interventions for benign prostatic hyperplasia (BPH). However, the validity and reliability of their ...

Learn how acceptance sampling improves quality control by evaluating random samples. Discover its methods, benefits, and historical significance in manufacturing.

Objective: The purpose of this systematic review and meta-analysis was to investigate the diagnostic performance of artificial intelligence models for multilevel pain assessment from facial images.