Artificial Intelligence Medical Compendium

Explore the latest research on artificial intelligence and machine learning in medicine.

Showing 1,151 to 1,160 of 200,219 articles

Bridging Acoustic and Semantic Spaces for Interpretable Voice Scoring via Zero-Shot Semantic Expansion

medRxiv Jun 1, 2026
Subjective auditory-perceptual evaluation and uninterpretable deep learning models limit the clinical assessment of voice disorders. This study proposes a two-phase zero-shot framework to evaluate voice pathology. First, an Audio Spectrogram Transfor... read more 
health informatics

Relationship Extraction for Adverse Drug Events in Clinical Notes Using Large Language Models

medRxiv Jun 1, 2026
Background: Adverse drug events (ADEs) are a critical indicator of patient safety but are often documented only in free-text clinical notes. The potential of recent advances in natural language processing (NLP), particularly generative large language... read more 
health informatics

Real-world impact of a sepsis early detection model integrated into clinical workflow: a quasi-experimental study

medRxiv Jun 1, 2026
Background: Sepsis is a life-threatening condition in which delayed recognition and treatment are associated with increased mortality. While predictive models such as Epic's Early Detection of Sepsis Model (ESM) were developed to support early interv... read more 
health informatics

Operationalizing Eight-Dimensional Patient-Safety Risk Scoring at Scale: A Multi-Model Large Language Model Reliability Study

medRxiv Jun 1, 2026
Background: Hospital incident risk scoring has long relied on two- or three-dimensional frameworks (Severity Assessment Codes or Risk Priority Numbers),even though root cause analysis standards recognize that clinical risk is multi-factorial. The obs... read more 
health informatics

Case-level artificial intelligence for multi-photo teledermatology submissions: development and internal validation using patient-submitted dermatology images

medRxiv Jun 1, 2026
Background: Store-and-forward teledermatology commonly relies on several patient-submitted photographs of the same concern, but most dermatology artificial intelligence models classify single images independently. Objective: To develop and internally... read more 
dermatology

Reliability and Concurrent Validity of a Computer Vision-Based Tool for Quantitative Finger Movement Analysis

medRxiv Jun 1, 2026
Background: Accurate evaluation of fine motor abilities is a key aspect of neurological rehabilitation. However, conventional approaches like goniometry are limited by variations among raters and their difficulty in detecting active movement. On the ... read more 
rehabilitation medicine and physical therapy

Developing and Evaluating Deep Learning Approaches for Visual Field Denoising in Glaucoma

medRxiv Jun 1, 2026
Purpose To investigate the relative efficacy of nine distinct visual field (VF) denoising artificial intelligence (AI) methods and a pathology-aware AI strategy to discourage over-correction of glaucomatous defects. Design Retrospective study. Partic... read more 
ophthalmology

Multi-Agent AI for Chest Radiography: A Sequential Segmentation and LLM-Driven Consultative Tool for Medical Training

medRxiv Jun 1, 2026
Background: Traditional diagnostic models lack explainability, while multimodal language models prone to hallucination remain unsafe for medical education. An interactive, risk-free artificial intelligence framework is required to serve as a reliable... read more 
health informatics

Stigmatizing Language Detection in Opioid Use Disorder Patient-Directed Discharge Clinical Documentation: A Privacy-Preserving Analysis Using a Locally Deployed Large Language Model

medRxiv Jun 1, 2026
Objective: Stigmatizing language in the electronic health record (EHR) has been associated with adverse patient experience in substance use disorder care, including opioid use disorder (OUD). This study evaluated a privacy-preserving, locally-deploye... read more 
health informatics

SeGA-GNN: Semantically Gated Augmented Graph Neural Networks for Wearable-Based Emotion Detection

medRxiv Jun 1, 2026
Background: Wearable technologies enable scalable and continuous monitoring of emotional states through passive sensing of physiological and behavioral signals. However, conventional learning approaches often struggle to model the complex temporal, c... read more 
health informatics
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