Artificial Intelligence Medical Compendium

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

Showing 23,131 to 23,140 of 217,176 articles

Coordinated human prefrontal dynamics sustain task-state representations during learning

bioRxiv May 5, 2026
Making decisions in complex, real-world environments is challenging. Biologically plausible strategies like reinforcement learning (RL) require attention toward reward-predictive stimuli to define task states, yet how attention and decision processes... read more 
neuroscience

EffectorGeneP: accurate gene annotation in pathogen genomes from infection transcriptomes

bioRxiv May 5, 2026
Accurate gene annotation is crucial for inference of biological knowledge from genomes. However, non-canonical genes such as orphan or single-exon genes as well as those residing in rapidly evolving regions are routinely dismissed in annotation pipel... read more 
microbiology

Do Larger Models Really Win in Drug Discovery?A Benchmark Assessment of Model Scaling in AI-Driven Molecular Property and Activity Prediction

bioRxiv May 4, 2026
The rapid growth of molecular foundation models and general-purpose large language models has encouraged a scale-centric view of artificial intelligence in drug discovery, in which larger pretrained models are expected to supersede compact cheminform... read more 
bioinformatics

A generative reference grammar of healthy TCR repertoires reveals cancer-associated immune remodeling

bioRxiv May 4, 2026
T-cell receptor (TCR) repertoires encode the organization of adaptive immunity and its reshaping by cancer and therapy, but disentangling treatment-associated structure from V(D)J recombination constraints remains challenging. We present CRAFT (Cance... read more 
cancer biology

Autonomous error detection is enabled by conflict-dependent forward models in human medial frontal cortex

bioRxiv May 4, 2026
Learning from mistakes is fundamental for survival. Humans can monitor their behavior to detect action errors without external feedback, utilizing error information for adaptation and learning. How such errors are detected remains unknown. We investi... read more 
neuroscience

A Scalable Sign-Aware Multi-Omics Knowledge Graph Foundation Model for Mechanistic Drug Action and Clinical Response Predictions

bioRxiv May 4, 2026
Mechanistically predicting the consequences of drug action requires distinguishing whether molecular interactions are activating or inhibitory, yet most biomedical knowledge graphs and graph neural networks represent biology as unsigned associations.... read more 
systems biology

Automatic Bevacizumab Response Prediction in Ovarian Cancer from Digital Pathology Images via Novel AI-based Computational Pipeline

bioRxiv May 4, 2026
Ovarian cancer is one of the gynecological cancer types, which, if metastasized and not detected early, can cause deaths among women. Therefore, there is a need to accurately predict drug responses to ovarian cancer. A gynecological pathologist inspe... read more 
bioinformatics

Joint Variable Selection for Omic Biomarkers in Time-to-Event Data

bioRxiv May 4, 2026
The incidence of the vast majority of neurodegenerative, cancer, and metabolic diseases generally increases exponentially with age. In large-scale biobanks, linking time-to-diagnosis information in electronic health records to multiple genomic (``mul... read more 
bioinformatics

Dual GLP-1/FGF21 agonism suppresses voluntary alcohol consumption, alcohol choice, and nucleus accumbens dopamine modulation

bioRxiv May 4, 2026
Excessive alcohol consumption remains a major public health challenge with limited therapeutic options. Both glucagon-like peptide-1 (GLP-1) and fibroblast growth factor-21 (FGF21) independently regulate alcohol intake through complementary metabolic... read more 
animal behavior and cognition

LNGCN: A Distance-Aware Dynamics Network for Protein-Protein Interaction Prediction

bioRxiv May 4, 2026
High-throughput accurate protein-protein interaction (PPI) prediction is foundational to systems-level biological understanding, disease mechanism dissection, and structure-based drug discovery. Traditional graph convolutional networks (GCNs) are lim... read more 
bioinformatics
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