Artificial Intelligence Medical Compendium

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

Showing 19,881 to 19,890 of 215,899 articles

A Blood-Based Transcriptomic Signature for PTSD Classification Using Machine Learning

medRxiv May 13, 2026
Post-traumatic stress disorder (PTSD) remains a significant psychiatric burden; despite growing biomarker research, no blood-based molecular diagnostic tool has been clinically validated for routine use. In this study, we developed a machine learning... read more 
health informatics

SIGNAL: A Scalable, Real-World Model for Rapid Intraoperative Molecular Classification of Gliomas Using Stimulated Raman Histology

medRxiv May 13, 2026
Background: Previous machine learning models to intraoperatively predict the molecular status of gliomas using stimulated Raman histology (SRH), such as DeepGlioma, have achieved high performance (91.5% accuracy) on curated datasets. However, when us... read more 
oncology

Structured large language model extraction of clinical factors from electronic health record text supports scalable psychiatric severity prediction

medRxiv May 13, 2026
Background: Mental health systems face escalating demand that exceeds clinician capacity, making accurate severity-based triage a critical bottleneck. Severity assessment guides treatment intensity, resource allocation, and risk management, yet most ... read more 
psychiatry and clinical psychology

Improving machine learning and deep learning models for 30-day ICU readmission prediction using Ensemble Bayesian Model Averaging

medRxiv May 13, 2026
Intensive Care Unit (ICU) readmissions are associated with adverse clinical outcomes and increased healthcare costs. Although existing models for predicting 30-day ICU readmission show high predictive performance, they fail to account for model uncer... read more 
intensive care and critical care medicine

From naive to foundation: benchmarking models for epidemic forecasting

medRxiv May 13, 2026
We systematically evaluate and compare the performance of classical statistical methods (ARIMA), mechanistic compartmental models (SEIR), modern deep learning architectures (LSTM, DLinear, Autoformer), and an emerging time-series foundation model (Ta... read more 
epidemiology

Video-based Detection of Delirium in Hospitalized Adults

medRxiv May 13, 2026
Delirium, a dynamic neuropsychiatric condition associated with morbidity and mortality, remains underdiagnosed due to reliance on subjective, intermittent screening tools. Objective and potentially continuous identification is needed to improve clini... read more 
geriatric medicine

A transformer model explaining mechanisms of drug therapeutic and adverse effects

medRxiv May 13, 2026
Understanding which disease genes are altered by a drug can provide insight into the biology of effect, help us understand adverse drug effects, and suggest new drug uses. Here, we build on our model Draphnet in a new formulation with a similar goal.... read more 
genetic and genomic medicine

Multimodal Wearable System for Objective Assessment of Dynamic Rotational Knee Biomechanics Following ACL Injury and Reconstruction: A Clinical Validation Study Using Ensemble Deep Learning

medRxiv May 12, 2026
ABSTRACT Background The clinical assessment of knee stability after an Anterior Cruciate Ligament (ACL) injury is routinely conducted via operator-dependent physical examination tests (i.e. pivot shift) and standardized patient-reported outcomes. Unf... read more 
orthopedics

Development of a Deep Learning Model Integrating CT Images and Blood Data for the Diagnosis of Acute Cholecystitis

medRxiv May 12, 2026
Purpose: In this study, we aimed to develop and evaluate an artificial intelligence-based diagnostic model for the diagnosis of acute cholecystitis (AC) using non-contrast CT images and clinical data. Materials and Methods: This retrospective study i... read more 
radiology and imaging

Epidemiology-Informed Graph Neural Networks for Predicting and Interpreting Transmissible Hospital-Acquired Infections: A Retrospective Cohort and Simulation Study

medRxiv May 12, 2026
Transmissible hospital-acquired infections (HAIs) arise from complex, time-varying interactions among patients, healthcare workers, and clinical environments. Although data-driven approaches like graph neural networks (GNNs) effectively model these c... read more 
health informatics
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