Latest AI and machine learning research in public health & policy for healthcare professionals.
Opioid misuse remains a critical public health concern, associated with increased risk of overdose, ...
Sleep, physical activity, and nutrition (SPAN) are major modifiable risk factors for cardiovascular ...
Dengue fever remains a critical public health challenge in Thailand, with transmission dynamics driv...
The health consequences of ionizing radiation have long been studied, yet significant uncertainties ...
The COVID-19 pandemic highlighted the critical need for robust methods to monitor viral evolution an...
Dengue remains a major public health concern in Bangladesh, yet reliable forecasting models that int...
This scoping review explores how predictive modelling can strengthen pre-exposure prophylaxis (PrEP)...
Adolescent mental health represents a global public health crisis, yet traditional surveillance meth...
Dengue remains a major public health challenge in southern Taiwan, where recurrent outbreaks are sha...
Antimicrobial resistance (AMR) poses a significant public health challenge, particularly in resource...
Cardiac allograft rejection (CAR) remains the leading cause of early graft failure after heart trans...
The public health impact of vaping in the United States reflects a complex balance of potential bene...
Multiple sclerosis (MS) is a chronic autoimmune disease of the central nervous system. Early detecti...
Hypertension (HTN) is a leading, yet often underdiagnosed, cause of cardiovascular diseases worldwid...
Information from electronic health records (EHRs) may be incorporated into computable phenotype algo...
Type 2 diabetes mellitus (T2DM) affects almost half a billion people, and the projected cost is $2.2...
Large language models (LLMs) have demonstrated rapid advancements in natural language understanding ...
Postoperative atrial fibrillation (POAF) affects 20 to 50% of patients undergoing cardiac surgery an...
Childhood maltreatment is a well-established risk factor for substance misuse. However, it remains u...
Sensitivity analysis is a key tool for identifying which model inputs most strongly influence model ...
To evaluate whether machine learning (ML) applied to comprehensive claims data without diagnostic co...