Artificial Intelligence Medical Compendium

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

Showing 10,381 to 10,390 of 209,311 articles

Interpretable morphology mapping of peripheral blood leukocytes using annotation-efficient artificial intelligence

bioRxiv
Background Peripheral blood smears (PBS) review is labor-intensive, subjective, and challenging for rare or morphologically heterogeneous cell types in hematologic malignancies. Artificial intelligence (AI) offers a scalable alternative, but broader ... read more 

Constrained protein Large Language Model illustrated in protein stability, function and epistasis

bioRxiv
Our understanding of protein function and evolution is largely based on the relationship between amino acid sequence and overall fold, now effectively captured by computational models. Yet predicting how mutations--shaped by epistasis--alter protein ... read more 

OryzaG3: A Single-species Genomic Foundation Model Pretrained on Rice Pangenome

bioRxiv
While multi-species genomic language models have advanced biological representation learning, high-quality, single-species foundation models for crops remain scarce. Leveraging recently expanded rice pangenome resources, we introduce OryzaG3, a speci... read more 

Multi-Algorithm Machine Learning Benchmarking for Pan-Cancer Classification from Tumour-Educated Platelet RNA Sequencing

bioRxiv
Tumour-educated platelets (TEPs) carry cancer-type-specific RNA signatures accessible through whole-blood RNA sequencing, but systematic multi-algorithm benchmarking with quantified statistical uncertainty had not been applied to the GSE68086 dataset... read more 

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

bioRxiv
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 

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

bioRxiv
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 

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

bioRxiv
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 

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

bioRxiv
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 

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

bioRxiv
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 

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

bioRxiv
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