Artificial Intelligence Medical Compendium

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

Showing 7,951 to 7,960 of 207,819 articles

Sensitive Glioma Detection and Recurrence Monitoring Using a Machine Learning Model Based on Circulating Monocytes

medRxiv Jun 1, 2026
Background: Non-invasive diagnosis, reliable recurrence surveillance remain critical unmet needs in gliomas. Glioma induces profound systemic immune alterations despite its anatomical confinement to the central nervous system. Circulating immune cell... read more 
oncology

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

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

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

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

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

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

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

AI-Guided Structure-Aware Modeling and Thermal Proteomics Reveal Direct Demethylzeylasteral-ACLY Interaction

bioRxiv Jun 1, 2026
Identifying the direct molecular targets of bioactive natural products remains a central challenge in chemical biology. Here we present an integrated experimental-computational framework, that combines matrix-augmented thermal proteomics with HoloGNN... read more 
biochemistry

Optimising Retraining Frequency for a Paediatric Emergency Department Admission Prediction Model: Development and Temporal Validation Using Real-World Data.

Emergency medicine Australasia : EMA Jun 1, 2026
OBJECTIVE: To analyse temporal performance drift and optimal retraining frequency for an ensemble machine learning model to predict inpatient admission from paediatric emergency department (ED) triage data. METHODS: This study utilised 409,307 ED pre... read more 
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