While previous studies have reported functional abnormalities in the prefrontal-limbic-subcortical circuit, the treatment effects on this activity remain unclear. This longitudinal study aimed to investigate spontaneous brain activity in bipolar diso...
BACKGROUND: Coronary artery disease (CAD) is one of the biggest causes of mortality worldwide. Risk stratification for early detection is essential for the primary prevention of CAD. QRISK3 is known to overestimate future CAD risk in some populations...
BACKGROUND: Experiences of unfair treatment on college campuses are linked to adverse mental and physical health outcomes, highlighting the need for interventions. However, detecting such experiences relies mainly on self-reports. No prior research h...
BACKGROUND AND OBJECTIVE: Bangladesh, a South Asian country, continues to face significant challenges in maternal health, as reflected by its high maternal mortality ratio (MMR). According to the 2022 Bangladesh Demographic and Health Survey (BDHS), ...
BACKGROUND: As medical education evolves, current teaching practices often remain misaligned with how today's digitally native students prefer to learn. While the use of digital tools is widespread, there is limited clarity on students' learning beha...
We evaluated the potential utility of imaging parameters derived by normalizing muscle signal intensity on T1-weighted lower leg MRIs in Charcot-Marie-Tooth disease type 1 A (CMT1A) patients, using a deep learning-based automated muscle segmentation ...
This study investigates the relationship between AI ethics literacy and students' self-rated learning competence using AI by developing a comprehensive framework of AI ethics literacy comprising knowledge, attitude, and competence dimensions. Data we...
Understanding the psychological effects of martial arts training requires models that can bridge the gap between observable physical behavior and subjective cognitive states. This study proposes a deep learning framework that explicitly uses question...
Given the prevalence of depression among young adults, particularly those aged 18-25, this study aims to address a critical need in higher education institutions for proactive, private, automated mental health self-awareness. This study protocol outl...
INTRODUCTION: Hypertension is a leading contributor to maternal and cardiometabolic morbidity in Bangladesh. We developed and interpreted machine-learning (ML) models to predict hypertension and rank associated factors among married women with the go...
Join thousands of healthcare professionals staying informed about the latest AI breakthroughs in medicine. Get curated insights delivered to your inbox.