Artificial Intelligence Medical Compendium

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

Showing 11,311 to 11,320 of 209,934 articles

Using Disinhibition versus Direct Control in a Spiking Neural Model of Dopamine-Driven Reinforcement Learning

bioRxiv May 26, 2026
Dopaminergic signalling is central to value learning and decision making. It has been observed that multiple pathways with different patterns of connectivity project to midbrain dopaminergic neurons, some involving direct excitatory projections while... read more 
neuroscience

Phylogenetically Dispersed Subsetting for Species-Level Machine Learning Evaluation: Dependence-Aware Validation and Limited Effective Information

bioRxiv May 26, 2026
Machine learning is increasingly applied to species-level biological data, but phylogenetic autocorrelation can make evaluation species statistically non-independent, violating the assumption of independence in model evaluation and potentially leadin... read more 
evolutionary biology

Beyond the annotated: protein foundation models enable robust prediction of microbial root competence

bioRxiv May 26, 2026
Background Root competence, the ability of soil bacteria to establish and grow on plant roots, is a key ecological trait influencing plant nutrition, growth, and health. However, identifying genomic determinants of root competence across bacteria rem... read more 
genomics

ARACoFusion: Uncertainty-aware calibrated deep learning for protein-protein interaction network prediction in Arabidopsis thaliana

bioRxiv May 26, 2026
Accurate mapping of the Arabidopsis thaliana protein-protein interaction (PPI) network is essential for deciphering complexity of plant systems biology. Here, we present ARACoFusion, a specialized deep learning architecture designed to predict inter-... read more 
bioinformatics

Sparse, trainable subnetworks for multi-omics integration: a cross-validated evaluation of the Lottery Ticket Hypothesis across nutrigenomic, toxicogenomic, and oncogenomic datasets

bioRxiv May 26, 2026
Multi-omics integration, the joint analysis of two or more high-dimensional molecular data types collected on the same biological samples, is now a standard analytical approach across nutrigenomics, toxicogenomics, microbiome research, and disease ge... read more 
bioinformatics

Beyond natural amino acids: Extending immunogenicity risk assessment to non-canonical peptide drugs through chemical feature encoding

bioRxiv May 26, 2026
Peptide therapeutics are increasingly used to treat challenging diseases, but immunogenicity risks limit their clinical success. In silico tools enable immunogenicity screening through prediction of peptide-MHCII binding, yet current methods fail to ... read more 
bioinformatics

AI-based Psychiatric Prediction in Youth: Neuroimaging Provides Minimal Gains Beyond Confounds

bioRxiv May 26, 2026
Recent advances in artificial intelligence (AI) have raised interest in its potential to similarly progress biological psychiatry. This study investigates the current utility of AI models in predicting psychiatric phenotypes in youth - a critical win... read more 
neuroscience

Molecular Characterization of T-Lineage Acute Lymphoblastic Leukemia by an Optimal-Transport Based Multi-Omics Integration Framework

bioRxiv May 26, 2026
T-lineage acute lymphoblastic leukemia (T-ALL) is an aggressive pediatric malignancy characterized by complex heterogeneity across multiple molecular layers. Accurate subtyping is essential for understanding disease mechanisms, risk stratification, a... read more 
bioinformatics

Whole slide image analysis of the endometrial decidual reaction reveals multiscale perturbations associated with miscarriage

bioRxiv May 26, 2026
The inflammatory decidual reaction renders the cycling endometrium transiently permissive for embryo implantation before transforming it into the decidua, the maternal bed accommodating the fetal placenta during pregnancy. Disruptions in decidual tis... read more 
pathology

dbGIST: An LLM-Assisted Multi-Omics Resource for Target Exploration and Cross-Dataset Validation in Gastrointestinal Stromal Tumors

bioRxiv May 26, 2026
Gastrointestinal stromal tumors (GISTs) are the most common mesenchymal neoplasms of the gastrointestinal tract, yet GIST-specific omics evidence remains scattered across small cohorts and is not represented as a dedicated disease project in major ca... read more 
cancer biology
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