Objectives To determine the scope of the application of natural language processing to free-
text clinical notes in post-acute care and provide a foundation for future natural language …

Transformers and large language models (LLMs) are increasingly used for clinical data
analysis, mostly in English, but also in many other languages used within medical care …

PURPOSE Identifying cancer symptoms in electronic health record (EHR) narratives is
feasible with natural language processing (NLP). However, more efficient NLP systems are …

Objectives Little is known about proactive risk assessment concerning emergency
department (ED) visits and hospitalizations in patients with heart failure (HF) who receive …

Objectives This study aims to evaluate the fairness performance metrics of Machine
Learning (ML) models to predict hospitalization and emergency department (ED) visits in …

Background Patients with heart failure (HF) who actively engage in their own self-
management have better outcomes. Extracting data through natural language processing …

Advance care planning, involving goals-of-care and surrogate-designation conversations, is
crucial for patient-centered care. However, determining the optimal timing and participants …

Objectives Home health care (HHC) serves more than 5 million older adults annually in the
United States, aiming to prevent unnecessary hospitalizations and emergency department …

A low survival rate of heart failure (HF) is attributed to the under-diagnosis due to lack of the
diagnostic reference standard. Heart failure usually is not well-documented in the …

The integration of chatbots into healthcare settings has garnered significant attention due to
their potential to improve patient engagement, provide timely information, and enhance …