Artificial Intelligence Medical Compendium

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

Showing 53,911 to 53,920 of 225,930 articles

Applying Artificial Intelligence to Facial Feminization Surgery: Understanding of Facial Anatomy, Surgical Techniques, and Patient Education.

Facial plastic surgery & aesthetic medicine
BACKGROUND: Artificial intelligence (AI) and machine-learning technology are on the rise, including ChatGPT and Google's Gemini, previously known as Bard. While recent studies have begun to explore the role of AI in medicine, there are no studies to ... read more 

Optimizing machine learning-based identification of sexual health influencers for HIV self-testing distribution among men who have sex with men in China: a secondary analysis of a quasi-experimental trial.

Sexual health
BACKGROUND: Secondary distribution of HIV self-testing can expand testing among men who have sex with men. A parent quasi-experimental trial found that sexual health influencers (SHIs) identified by a machine-learning model achieved greater peer upta... read more 

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

bioRxiv
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 

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

bioRxiv
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 

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

bioRxiv
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 

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

bioRxiv
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 

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

bioRxiv
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 

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

bioRxiv
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 

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

bioRxiv
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 

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

bioRxiv
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