Artificial Intelligence Medical Compendium

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

Showing 53,541 to 53,550 of 225,548 articles

Using Artificial Intelligence to optimize agreement between interstitial sensors and capillary puncture in glycemic assessment and classification

medRxiv Feb 5, 2026
Introduction: Blood glucose monitoring is essential for the management of diabetes mellitus. Continuous interstitial glucose (IG) monitoring systems are less invasive than capillary blood glucose (BG) measurements, but their agreement decreases at hi... read more 
endocrinology

Automated Ventricle Assessment via Three-dimensional Anatomical Reconstruction (AVA-TAR): a computational toolkit for autonomous lateral ventricle assessment in preclinical hydrocephalus models

bioRxiv Feb 5, 2026
Introduction: Current workflows for studying hydrocephalus in rodent models rely on manual segmentation or qualitative assessment of ventricular size on small animal magnetic resonance imaging, which are both inefficient and prone to variability. Atl... read more 
neuroscience

Predicting Post-Stroke Aphasia Speech Performance from Multimodal Data with Explainable Machine Learning

bioRxiv Feb 5, 2026
Aphasia, an acquired language deficit, is the most common post-stroke focal cognitive impairment, and roughly 60% cases become chronic (duration >6 months). Aphasia therapies could be optimized if clinicians could make personalized predictions of how... read more 
bioengineering

A Shape Analysis Algorithm Quantifies Spatial Morphology and Context of 2D to 3D Cell Culture for Correlating Novel Phenotypes with Treatment Resistance

bioRxiv Feb 5, 2026
Numerous studies have shown that the morphological phenotype of a cell or organoid correlates with its susceptibility to anti-cancer agents. However, traditional methods of measuring phenotype rely on spatial metrics such as area, volume, perimeter, ... read more 
bioinformatics

Model Ensembling and Machine Learning Approaches to Predict the First Dose of Amoxicillin in Intensive Care

bioRxiv Feb 5, 2026
A priori model informed precision dosing (MIPD) recommends an appropriate first dose based solely on the covariates of the patient enabling faster target attainment without required concentration measurements. Population pharmacokinetic model ensembl... read more 
pharmacology and toxicology

Bootstrap resampling of mass spectral pairs with SpecReBoot reveals hidden molecular relationships

bioRxiv Feb 5, 2026
Mass spectral molecular networking (MN) has emerged as a key computational approach to organize and analyze the vast volumes of tandem mass spectrometry (MS/MS) data generated in natural product research. MN connections are based on mass spectral sim... read more 
biochemistry

Live high-content imaging with automated analysis reveals mitochondrial changes during vascular calcification

bioRxiv Feb 5, 2026
Mitochondrial dysfunction is implicated in a wide range of disorders, including cancer, neurodegeneration, and cardiovascular diseases. Conventional assays typically assess mitochondrial function by measuring bulk respiration rates across thousands o... read more 
cell biology

Comparing metabolic engineering scenarios using simulated design-build-test-learn-cycles

bioRxiv Feb 5, 2026
Design-Build-Test-Learn (DBTL) cycles are a widely employed engineering framework in metabolic engineering. Nonetheless, their performance depends on a wide range of experimental and algorithmic design choices, whose combined effects on the successfu... read more 
bioengineering

BioVix: An Integrated Large Language Model Framework for Data Visualization, Graph Interpretation, and Literature-Aware Scientific Validation

bioRxiv Feb 5, 2026
The application of Large Language Models (LLMs) for generating data visualizations through natural language interaction represents a promising advance in AI-assisted scientific analysis. However, existing LLM-based tools largely emphasize graph gener... read more 
bioinformatics

Modeling the inverse MEG problem in neuro-imaging using Physics Informed Neural Networks

bioRxiv Feb 5, 2026
Magnetoencephalography (MEG) forward and inverse modeling is fundamental to neuroscientific discovery, yet the inversion of partial differential equations (PDEs) remains one of the most difficult challenges due to its inherent ill-posedness. While tr... read more 
neuroscience
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