Latest AI and machine learning research in information technology for healthcare professionals.
The International Forum of Internal Medicine (FIMI) presents a position paper that analyzes the current state and projects the future of Internal Medicine in a global context marked by population aging, multimorbidity, fragmentation of health systems, and rapid technological transformation. The document emerged from a collaborative process involving 52 scientific societies from 43 countries, with ...
BACKGROUND: Opioid overdose remains a leading cause of preventable death in the United States. Existing approaches to identify individuals at elevated risk rely on imprecise rule-based criteria that misclassify patients' risk of this serious health outcome. Machine learning (ML) algorithms can help improve prediction performance and can be combined with electronic health record (EHR) interventions...
Managing patients with respiratory failure increasingly involves non-invasive respiratory support (NIRS) strategies to support respiration, often prev...
Wildfire management is undergoing rapid transformation as data fusion, artificial intelligence, and participatory approaches are used to enhance ecosy...
OBJECTIVES: Efficient exchange of health information requires consistent representation of clinical concepts across laboratories, hospitals, and publi...
Drug discovery remains a lengthy, costly, and high-risk endeavor, often requiring over a decade from target identification to clinical translation. Ar...
The last decade has seen rapid advancements in machine learning, significantly transforming fields like cybersecurity and healthcare. Developmental sc...
PURPOSE: Pharmacoepidemiology and population health studies using electronic health care records (EHRs) must define study variables through available ...
BACKGROUND: Pancreatic cancer is characterized by prolonged subclinical progression, molecular heterogeneity, and late clinical presentation, resultin...
Prolonged exposure to electronic devices exacerbates neck health issues in modern populations. To address this challenge, we develop a flexible strain...
Cardiogenic shock (CS) remains the leading cause of mortality in modern cardiac intensive care unit, most often precipitated by acute or chronically d...
As the healthcare sector increasingly integrates Artificial Intelligence (AI) technologies to improve operational effectiveness, diagnosis, and therap...
BACKGROUNDS: Physicians are among the most vital healthcare resources. The equitable distribution of human resources could help policymakers to reach ...
The vast potential of observational healthcare data in biomedical discovery remains largely unrealized because clinical records are fragmented, unstru...
Chemotherapy is essential for cancer treatment but may cause adverse events requiring emergency department visits and hospitalizations, placing substa...
OBJECTIVE: To critically evaluate advances in artificial intelligence (AI) within rhinology, focusing on translational readiness, regulatory alignment...
OBJECTIVE: The use of ambient AI documentation tools is rapidly growing in US hospitals and clinics. Such tools generate the first draft of clinical n...
BACKGROUND: Medication errors remain a leading source of preventable harm in hospitalized patients, contributing to adverse drug events (ADEs), prolon...
INTRODUCTION: In older adults with cancer, geriatric assessment (GA) can improve care quality. In-person assessment may not be feasible for all patien...