Artificial Intelligence Medical Compendium

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

Showing 9,691 to 9,700 of 208,614 articles

WITHDRAWN: Scalable Microbiome Network Inference: Mitigating Sparsity and Computational Bottlenecks in Random Effects Models

bioRxiv May 26, 2026
The application of Large Language Models (LLMs) and Transformers to biological and healthcare datasets requires the extraction of highly accurate, noise-filtered ecological networks. The Random Effects Model (REM) is a powerful statistical method for... read more 
bioinformatics

Automated sleep scoring in hibernating and non-hibernating American black bears

bioRxiv May 26, 2026
Hibernating bears show remarkable metabolic suppression. Their decline in core body temperature (Tb) is moderate(from 38{degrees}C to 30-35{degrees}C), but their metabolism declines as much as 75%. To understand the role of sleep in this hypometaboli... read more 
neuroscience

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

bioRxiv May 26, 2026
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 
bioinformatics

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

bioRxiv May 26, 2026
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 
bioinformatics

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

bioRxiv May 26, 2026
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 
bioinformatics

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
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