Artificial Intelligence Medical Compendium

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

Showing 47,001 to 47,010 of 224,199 articles

Patient-centric radiology: Utilising large language models (LLMs) to improve patient communication and education

medRxiv
Purpose: To evaluate whether large language models (LLMs) can enhance clinician-patient communication by simplifying radiology reports to improve patient readability and comprehension. Methods: A randomised controlled trial was conducted at a single ... read more 

Care Plan Generation for Underserved Patients Using Multi-Agent Language Models: Applying Nash Game Theory to Optimize Multiple Objectives

medRxiv
Background Clinicians in care management programs are often in low supply relative to patient demand, especially in US Medicaid programs, and must simultaneously address clinical risk, time efficiency, and patients' social needs. Many studies have sh... read more 

Large-Language Models for data extraction from written kidney biopsy reports

medRxiv
Introduction: Kidney biopsy reports contain rich information that is clinically actionable and useful for research. However, the narrative format hinders scalable reuse. We here investigated whether open-source large language models (LLMs) can extrac... read more 

Unsupervised Machine Learning of Computed Tomography Angiography Features Uncovers Unique Subphenotypes of Aortic Stenosis With Differential Risks of Conduction Disturbances Following Transcatheter Aortic Valve Replacement

medRxiv
Background: Various measurements around the aortic valve are typically made on computed tomography angiograms (CTAs) before transcathether aortic valve replacement (TAVR) for aortic stenosis (AS), but their collective prognostic inference on periproc... read more 

High-Resolution Coastal Blue Carbon Site Intelligence: A Multi-Attribute Geospatial Pipeline for National-Scale Mangrove Assessment

bioRxiv
The voluntary blue carbon market is severely bottlenecked by outdated methodologies that apply broad, coast-level carbon averages across low-resolution spatial units, systematically failing to account for micro-site ecological realities and critical ... read more 

Spontaneous emergence of topographic organization in a multistream convolutional neural network

bioRxiv
Neurons in the cerebral cortex are organized topographically. In the primate visual cortex, neighboring neurons often respond to similar stimulus parameters, such as receptive field position, orientation, color, and spatial frequency. Preferred stimu... read more 

ARCH3D: A foundation model for global genome architecture

bioRxiv
Biological foundation models are transforming scientific discovery by creating information-rich representations that enable inference in low-data settings. Progress on these models has mainly been achieved by increasing input contextual information, ... read more 

Using machine learning to automate the analysis of an olfactory habituation-dishabituation task in mice

bioRxiv
Introduction Improving the efficiency and accuracy of annotation and extraction of performance data from mouse behavioural tasks will improve both the throughput and scientific value of preclinical research. Methods Here, we present and validate an a... read more 

RNA foundation models enable generalizable endometriosis disease classification and stable gene-level interpretation

bioRxiv
Endometriosis is a chronic inflammatory condition with significant diagnostic delays impacting one in ten reproductive age women worldwide. While machine learning (ML) models trained on transcriptomic data show promise for disease prediction, limited... read more 

Longitudinal modality prediction learns gene regulatory patterns: insights from a single-cell competition

bioRxiv
Simultaneous measurement of chromatin, transcriptomic, and proteomic features in single cells opens new avenues for modeling interactions between molecular layers during dynamic biological processes. Predicting one modality from another - such as inf... read more