Latest AI and machine learning research in medicolegal for healthcare professionals.
Large Language Models (LLMs), represented by the Generative Pretrained Transformer (GPT), are profoundly transforming the healthcare sector. Spine medicine, a discipline heavily reliant on complex imaging data, detailed clinical records, and evidence-based medical practice, serves as an ideal testing ground for exploring and applying these advanced artificial intelligence technologies. It holds th...
BACKGROUND: Technological advancements and legislation have led to the widespread use of electronic health records (EHRs) in the 21st century. Along with EHR implementation came improved health care quality, continuity of care, and data availability. However, EHRs are not without drawbacks. Physician burnout rates are rising, and EHRs are among the top causative factors. The consequences of burnou...
BACKGROUND: Sensor-based footwear is increasingly discussed as a promising tool for mobility monitoring and fall-risk assessment, yet its applicabilit...
Quantitative susceptibility mapping (QSM) on MRI quantifies tissue magnetic susceptibility, which increases with iron accumulation, myelin loss, and n...
G-protein-coupled receptors (GPCRs) are a diverse family of seven-transmembrane domain receptors that play pivotal roles in various physiological and ...
Threat detection is compromised across the schizophrenia spectrum, often revealed by paranoia and delusions. Threat difficulties extend to nonclinical...
Pathological and neuroimaging changes in the cerebellum of Alzheimer's disease (AD) patients have been well documented. However, the changes in cerebe...
Artificial intelligence (AI) is transforming task optimization across many occupations, particularly within the IT sector. Understanding how IT profes...
PURPOSE: Generative artificial intelligence (GenAI) is rapidly emerging as a transformative technology in aphasia management, necessitating judicious ...
Artificial intelligence (AI) offers a promising solution to the long-standing challenge of accurately predicting treatment response in rectal cancer. ...
PURPOSE OF REVIEW: Anesthesiology generates large volumes of heterogeneous perioperative data, including high-resolution physiological signals, clinic...
PURPOSE: Artificial intelligence (AI) scribes are being rapidly adopted in oncology, yet their real-world impact on physician productivity, workflow, ...
INTRODUCTION: Biosimilar stewardship includes safety, appropriate use, and value. However, it faces challenges due to shortages in disproportionality ...
Biomedical machine learning (ML) models raise critical concerns about embedded assumptions influencing clinical decision-making, necessitating robust ...
The porcine excisional wound model is widely regarded as the most translationally relevant preclinical platform for studying human skin wound healing ...
OBJECTIVE: This study presents a systematic review of natural language generation (NLG) methods and applications in the medical domain, providing quan...
BACKGROUND: Idiopathic Pulmonary Fibrosis (IPF) is a progressive and fatal interstitial lung disease characterized by excessive extracellular matrix (...
OBJECTIVE: Understand the qualitative impact of an ambient artificial intelligence (AI) documentation platform on clinicians' experiences and workflow...
Large language models (LLMs) are increasingly used by patients and families to interpret complex medical documentation, yet most evaluations focus onl...