Artificial Intelligence Medical Compendium

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

Showing 13,221 to 13,230 of 211,153 articles

Application of modern mathematical methods for species discrimination in the water fleas (Cladocera: Branchiopoda) that appear similar to the human eye: case of Bosmina (Bosmina) longirostris (O.F. Muller, 1776) from European Eurasia and Sakhalin Island

bioRxiv May 22, 2026
Intraspecific morphological variability presents a complex challenge for biological systematics and biomonitoring, particularly for organisms with high phenotypic plasticity, such as zooplankton. Morphological differences between individuals of the w... read more 
zoology

Internal state dynamically gates task-specific attractor dynamics in prefrontal cortex

bioRxiv May 22, 2026
Internal states such as motivation and task engagement influence cognitive functions. Working memory, which maintains information over time, is an essential component of cognition and is modulated by motivation. Here, we show motivational states modu... read more 
neuroscience

A Competitive Framework for Modeling EEG Microstate Durations

bioRxiv May 22, 2026
Background. This study examines a competition based model (Cmodel) designed to capture the temporal dynamics of successive brain microstates derived from electroencephalography (EEG) recordings during eyes-open conditions. The analyzed data were obta... read more 
neuroscience

A community machine learning challenge to predict the effects of gene perturbations on T cell differentiation for cancer immunotherapy

bioRxiv May 22, 2026
Perturbations of genes with functional importance in T cells could be used to change the distribution of CD8 T cell states to enhance anti-tumor functions for cancer immunotherapies. We launched a world-wide computational challenge to predict the eff... read more 
bioinformatics

Generalist large language models complement tailor-made predictors for tumor genomics interpretation

bioRxiv May 22, 2026
General-purpose large language models (LLMs) are trained on large corpora to acquire broad knowledge, but whether LLMs can replace, or augment, task-specific models is unclear. We evaluated LLMs on three real-world, clinically important tumor genomic... read more 
genomics

De novo design of RNA pseudoknots with deep learning

bioRxiv May 22, 2026
RNA design has been hindered by the limited accuracy of 3D structure prediction. Here, we show that intricate RNA structures can be generated with current deep learning tools through accurate de novo design of pseudoknot secondary structures. In an E... read more 
biophysics

Performance of IBD machine learning classifiers varies across microbiome training data independent of geographic diversity

bioRxiv May 22, 2026
Microbiome-based machine learning classifiers show increasing promise for disease identification across gastrointestinal, metabolic, and immune-mediated conditions. Inflammatory bowel disease (IBD), a chronic immune-mediated disorder associated with ... read more 
microbiology

A digital twin for hospital antimicrobial resistance forecasting and constrained intervention optimisation

medRxiv May 22, 2026
Hospital antimicrobial resistance (AMR) emanates from an array of complex interactions between patient turnover, heterogeneous patient--staff contact patterns, antibiotic-driven within-host selection, and imperfect surveillance. We present a hospital... read more 
public and global health

Evidence-Graded Decision Authorization for Safe Clinical AI: A Constrained Reasoning Framework

medRxiv May 22, 2026
Clinical AI systems have achieved strong predictive performance; however, prediction accuracy is not sufficient for clinical safety. Retrieval-augmented generation (RAG) improves factual accuracy, and general-purpose LLM guardrails constrain surface-... read more 
health informatics

Genetic architecture of high-dimensional liver radiomic phenotypes and their role in common metabolic diseases

medRxiv May 22, 2026
The liver plays a central role in systemic metabolism, yet large-scale genetic studies of quantitative liver imaging phenotypes remain limited. Here, we applied deep learning-based segmentation and radiomics extraction to derive 200 well-defined live... read more 
genetic and genomic medicine
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