Artificial Intelligence Medical Compendium

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

Showing 26,001 to 26,010 of 217,905 articles

Explainable 3D VGG-style convolutional neural network for pediatric hydrocephalus detection on computed tomography: A segmentation-free and fully volumetric deep learning framework.

Neuroscience Apr 26, 2026
Pediatric hydrocephalus is commonly assessed on computed tomography (CT) using manual two-dimensional indices that incompletely reflect the ventricular system. We developed and evaluated an explainable, segmentation-free three-dimensional convolution... read more 

Interpretable three-dimensional deep learning identifies and reveals the spatial Microstructure of multi-enzyme degradation of lignocellulose.

Bioresource technology Apr 26, 2026
Understanding the spatial mechanisms of multi-enzyme lignocellulose deconstruction is hindered by the lack of spatial quantification and nondestructive analytical methods. This study established an interpretable three-dimensional (3D) deep learning f... read more 

Valorization of artichoke processing by-products via production of oligosaccharide-enriched extracts optimized by artificial neural networks.

International journal of biological macromolecules Apr 26, 2026
Valorisation of agro-industrial by-products is central to circular-economy strategies. This study evaluates the potential of industrial artichoke by-products to yield oligo-fructan (OS-Fr)-enriched extracts and optimises production using artificial n... read more 

Machine learning classification of patients after suicide attempts using demographic data, EEG connectivity and heart rate variability.

Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology Apr 26, 2026
OBJECTIVE: The aim of this study was to develop a way to distinguish suicidal patients based on their electrophysiologic (EEG connectivity and heart rate variability) and demographic data. Various machine learning algorithms were compared to find the... read more 

AI-driven target definition using CE-T1w and black blood sequence imaging in stereotactic radiosurgery for brain metastases.

European journal of radiology Apr 26, 2026
OBJECTIVES: Development and evaluation of a deep learning-based method for automatic detection and target delineation of brain metastases on contrast-enhanced T1-weighted (CE-T1w) and black blood (BB) MR scans for optimization of stereotactic radiosu... read more 

Current and emerging therapies for knee osteoarthritis: From conventional approaches to machine learning and stem cell innovations.

Regenerative therapy Apr 26, 2026
Osteoarthritis is characterized by cartilage degradation and joint distortion. The most prevalent version of osteoarthritis, knee osteoarthritis (KOA), affects millions, acting as a leading cause of disability. With the average life expectancy contin... read more 

Examining user-AI interaction patterns in health-Information queries.

International journal of medical informatics Apr 26, 2026
In this study, we examine how individuals utilize generative artificial intelligence (GAI) when seeking health-related information. Using a dataset of user-GAI chat logs available on Hugging Face, we analyzed real-world interactions in which users po... read more 

Integrative Clinical-Molecular Modeling Identifies LRRN4CL as a Determinant of Structural and Functional Myocardial Improvement

bioRxiv Apr 26, 2026
Background: Mechanical ventricular unloading and systemic circulatory support with left ventricular assist devices (LVADs) enable myocardial recovery in a subset of advanced heart failure (HF) patients, but predictors and mechanisms of recovery are n... read more 
bioinformatics

GlioVision: A Multi-Modal MRI Framework for Non-Invasive Glioma Molecular Biomarkers Prediction

bioRxiv Apr 26, 2026
Gliomas are aggressive primary brain tumors that necessitate critical molecular biomarker predictions for optimal clinical decision-making. Traditional assessment relies on surgical tumor specimens analysis, which carries procedural risks and samplin... read more 
neuroscience

Decoding the phenomenology of spontaneous thought using large language-model ratings on verbal retrospective free reports

bioRxiv Apr 26, 2026
Spontaneous thoughts constitute most of everyday inner experience, yet long-standing methodological challenges obscure a thorough exploration of their content and neurophysiological underpinnings. Traditional approaches relying on thought probes impo... read more 
neuroscience
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