Latest AI and machine learning research in medicolegal for healthcare professionals.
Radiology Report Generation (RRG) through Vision-Language Models (VLMs) promises to reduce documentation burden, improve reporting consistency, and accelerate clinical workflows. However, their clinical adoption remains limited by the lack of interpretability and the tendency to hallucinate findings misaligned with imaging evidence. Existing research typically treats interpretability and accuracy ...
Background: Nursing documentation patterns may reflect patient acuity and clinical deterioration, yet their prognostic value remains underexplored. We developed the Intensive Documentation Index (IDI), a novel framework quantifying temporal documentation rhythms, and evaluated its ability to enhance ICU mortality prediction. Methods: We analyzed 26,153 ICU admissions of heart failure patients from...
Body mass index (BMI), type 2 diabetes (T2D) and associated cardiometabolic features modify Alzheimer's disease (AD) risk, yet shared mechanisms remai...
Background: Liver cancer primarily develops in patients with chronic liver disease (CLD), yet most cases are diagnosed at an advanced stage with poor ...
Rapid advances in bioinformatics have transformed biomedical research in areas such as single-cell and spatial omics, digital pathology, and multi-mod...
Large Language Models (LLMs) and Retrieval-Augmented Generation (RAG) systems are increasingly integrated into clinical workflows; however, prompt inj...
Importance: High-quality discharge summaries are essential for safe care transitions but contribute substantially to clinician documentation burden an...
Objective To characterize the clinical and administrative concerns communicated through secure ophthalmology messaging and to assess differences in me...
Motivation: Extracting knowledge from biomedical data is crucial for advancing our understanding of biological systems and developing novel therapeuti...
Difficulty replicating baselines, high computational costs, and required domain expertise create persistent barriers to clinical AI research. To addre...
Generative artificial intelligence (AI) is rapidly populating medical records with synthetic content, creating a feedback loop where future models are...
Generative artificial intelligence (AI) is rapidly populating medical records with synthetic content, creating a feedback loop where future models are...
Public health policies increasingly rely on the use of complex and large datasets containing heterogeneous, multimodal data that require advanced anal...
Foundation models trained on electronic health records show strong performance on many clinical prediction tasks but are limited by sparse and irregul...
Artificial intelligence (AI) has the potential to transform medical imaging by automating image analysis and accelerating clinical research. However, ...
BackgroundArtificial intelligence (AI) scribes have the potential to reduce documentation burden. Previous studies have mostly relied on aggregated, v...
The withering process is a critical stage in developing the aroma profile of black tea. In this study, we presented an eco-friendly cellulose film-bas...
Protein structure characterization is critical for therapeutic protein drug development and production. Drop-coating deposition Raman (DCDR) spectrosc...
Large language models (LLMs) such as GPT-4o and o1 have demonstrated strong performance on clinical natural language processing (NLP) tasks across m...
Large language models (LLMs) such as GPT-4o and o1 have demonstrated strong performance on clinical natural language processing (NLP) tasks across m...