Latest AI and machine learning research in hospitalists for healthcare professionals.
Introduction Secondary use of electronic health records (EHRs) often requires transforming raw clini...
Medical concept extraction from electronic health records underpins many downstream applications, ye...
Designing reward functions remains a central challenge in reinforcement learning (RL) for healthcare...
This study presents a fully automated methodology for early prediction studies in clinical settings,...
Background Chronic subdural hematoma (cSDH) recurrence requiring reoperation occurs in 5-33% of case...
Objective: To develop and validate a multivariable prediction model and clinically actionable risk s...
Background: Length of stay (LOS) is a critical metric for hospital operational efficiency. While str...
Objective: To evaluate a ranking approach for emergency department (ED) waiting room prioritization ...
Background: Cardiovascular disease (CVD) readmissions impose substantial clinical and economic burde...
Agentic AI systems are increasingly capable of autonomous data science workflows, yet clinical predi...
Background: Large language models (LLMs) are increasingly piloted as chat interfaces for chart revie...
Importance: High-quality discharge summaries are essential for safe care transitions but contribute ...
Background: Prognostic assessment in critically ill patients with cancer remains challenging, as con...
Generative models trained using self-supervision of tokenized electronic health record (EHR) timelin...
Accurate clinical prognosis requires synthesizing structured Electronic Health Records (EHRs) with r...
Background: Sarcopenia is associated with mortality and morbidity following acute ischemic stroke (A...
Sepsis remains one of the leading causes of mortality in intensive care units, where timely and accu...
BackgroundSystemic infections are a leading cause of hospitalization and death among patients with c...
The discharge of sulfate-rich wastewater from chemical and pharmaceutical and food processing indust...
Adverse events such as compulsory measures, absconding, illicit substance use, self-harm, aggressive...
Despite the remarkable performance of Large Language Models (LLMs) in automated discharge summary ...