Latest AI and machine learning research in obesity for healthcare professionals.
Objective: To evaluate modifiable antepartum and intrapartum factors associated with nulliparous, term, singleton, vertex (NTSV) cesarean delivery and to model risk stratified induction timing strategies that minimize cesarean risk across maternal risk profiles. Study Design: This retrospective cohort study included all NTSV deliveries at a tertiary care center from January 2015 through August 202...
Lifestyle and environmental factors such as diet, physical activity, residential greenspace exposure, alcohol consumption, and sleep are increasingly promoted as modifiable targets for maintaining cognitive health and mitigating age-related decline. Yet, it remains unclear how well they predict cognitive functioning and, importantly, to what extent their associations with cognition are reflected i...
Introduction: Recreational and medical cannabis use (CU) information is often available within the electronic health record (EHR) in a format that is ...
Psychiatric disorders are fundamentally challenged by symptom heterogeneity, high comorbidity, and the absence of objective biomarkers, which together...
Introduction: Cardiovascular diseases (CVDs) are the leading cause of death globally, with rising burdens in Africa due to ageing populations, lifesty...
Objectives: Artificial intelligence (AI) enabled digital stethoscopes combine phonocardiography and electrocardiography to support detection of cardia...
Perinatal depression (PD) is common and disabling, yet its longitudinal comorbidity patterns and predictability remain poorly understood. This study l...
Depression is a heterogeneous disorder, often diagnosed based on symptom co-occurrence. However, individuals may present with markedly different sympt...
We present MeFEm, a vision model based on a modified Joint Embedding Predictive Architecture (JEPA) for biometric and medical analysis from facial ima...
Neurological health score (NHS), indicating the health of brain and nervous system, helps in identifying high risk individuals, and in recommending li...
Body mass index (BMI), type 2 diabetes (T2D) and associated cardiometabolic features modify Alzheimer's disease (AD) risk, yet shared mechanisms remai...
INTRODUCTION: Cognitively unimpaired (CU) adults show substantial variation in their risk of developing mild cognitive impairment (MCI), yet most subt...
Loneliness and psychological well-being are increasingly recognized as critical public health concerns, yet their multi-factorial determinants remain ...
Brain machine interfaces (BMIs) aim to decode motor intentions from neural activity to enable direct control of external devices. However, most existi...
Accurate risk stratification in patients with overweight or obesity is critical for guiding preventive care and allocating high-cost therapies such as...
Background: Traditional pharmacovigilance methods based on biostatistical approaches systematically exclude outliers and rare events, potentially miss...
The human face is a rich medium for biometric, behavioral, and clinical information. However, 2D facial images based technologies lack critical geomet...
Pregnancy care often involves simultaneous obstetric and other medical conditions, but their co-occurrence patterns are rarely modeled explicitly in a...
Background- Eating timing and regularity represent new contributors to metabolic health, however, the time-based aspect of eating behavior is rarely i...
Background: Cardiovascular diseases (CVDs) remain the leading global cause of morbidity and mortality. In clinical practice, 10-year risk prediction t...