Latest AI and machine learning research in information technology for healthcare professionals.
Use of coercive measures in psychiatric hospitals is clinically and ethically challenging. Aiming to...
Depression is a leading cause of global disability. Timely identification of patients at risk for cl...
Disease management for heart failure with preserved ejection fraction (HFpEF) requires understanding...
Electronic health records (EHRs) provide a large source of data that can be used for research purpos...
The increasing availability of electronic health records (EHRs) provides opportunities to apply mach...
Diabetes mellitus remains a major global health burden, causing an estimated 3.4 million deaths in 2...
Ocrelizumab and natalizumab are commonly prescribed high-effectiveness disease-modifying therapies (...
Develop and deploy a real-time, EHR-integrated machine learning phenotype to identify emergency depa...
Rare neuromuscular diseases such as polyneuropathy (PN) and myopathy (MY) often share symptomatic ch...
The irreversible progression and profound societal impact of Alzheimer’s disease and related dementi...
Electronic health records (EHRs) contain years of longitudinal clinical notes that capture evolving ...
Peripheral artery disease (PAD) affects over eight million Americans and is a leading cause of non-t...
BACKGROUND: Limited universally-adopted data standards in veterinary medicine hinder data interopera...
OBJECTIVE: To develop a non-invasive, radiation-free model for early colorectal adenoma prediction u...
OBJECTIVE: Telemedicine platforms played a crucial role during the COVID-19 pandemic, alleviating is...
Advanced Persistent Threat (APT) malware attacks, characterized by their stealth, persistence, and h...
Artificial Intelligence (AI) is being integrated into increasingly more domains of everyday activiti...
A zero-day vulnerability is a critical security weakness of software or hardware that has not yet be...
BACKGROUND: Acute hepatic porphyria (AHP) is a group of rare but treatable conditions associated wit...
OBJECTIVE: This study aims to automate the prediction of Mini-Mental State Examination (MMSE) scores...
Accurate prediction of suicide risk is crucial for identifying patients with elevated risk burden, h...