Artificial Intelligence Medical Compendium

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

Showing 19,031 to 19,040 of 214,800 articles

STEM-LM: Spatio-Temporal Ecological Modeling via Masked Language Model for Joint Species Distribution

bioRxiv May 14, 2026
Joint species distribution models (JSDMs) are central to biodiversity forecasting and conservation decision-making. As ecological datasets grow in size, dimensionality, and spatio-temporal resolution, there is a need for flexible yet scalable JSDMs t... read more 
ecology

Uncertainty-aware graph representation learning with positive-unlabeled classification for biomarker discovery in peripheral artery disease

bioRxiv May 13, 2026
Peripheral artery disease (PAD) is a complex vascular disorder characterized by heterogeneous molecular mechanisms and incomplete functional annotation, limiting systematic biomarker discovery. Network-based learning approaches provide a powerful fra... read more 
systems biology

HAIRpred2: Human Host-Specific Prediction of Antibody-Interacting Residues Using Hybrid Physicochemical and Structural Features

bioRxiv May 13, 2026
Prediction of conformational B-cell epitopes is critical for vaccine design, immunotherapy, and antibody engineering. To date, several host-independent computational methods have been developed for predicting antibody-interacting residues in antigen ... read more 
bioinformatics

Transferable spatial omics deconvolution with SpaRank

bioRxiv May 13, 2026
By resolving cell-type compositions from multi-cellular spatial measurements, deconvolution is central to resolving the cellular landscape of complex tissues. Existing deconvolution methods fit continuous expression values and are therefore sensitive... read more 
bioinformatics

Shared roles and team membership are reflected in functional connectome similarity: Neural evidence from real-world volleyball teams

bioRxiv May 13, 2026
In task-oriented teams, long-term coordination among specialized roles may contribute to shared patterns of cognition and behavior, yet little is known about how such experience is reflected in brain functional organization. Here, we examined whether... read more 
neuroscience

Disease-guided functional gene mapping across species reveals translational correspondences beyond sequence orthology

bioRxiv May 13, 2026
Selecting the correct mouse gene to model a human disease phenotype is critical for translational research, yet sequence-based orthology can fail when genes have been lost, duplicated, or functionally rewired between species. Here we present BRIDGE (... read more 
bioinformatics

Tuning into the city soundscape: Optimizing Convolutional Neural Networks for avian acoustic identification in the neotropics and evaluating their performance against established monitoring approaches.

bioRxiv May 13, 2026
Convolutional Neural Networks (CNNs) have become increasingly prominent in biodiversity monitoring due to their strong performance in accurately detecting species from sound recordings, overcoming some limitations of traditional methods such as point... read more 
ecology

BiLSTM-Powered Bilinear Attention for Protein-Ligand Prediction

bioRxiv May 13, 2026
Rapid and accurate prediction of protein-ligand bindings is essential for drug discovery. While generative AI has driven rapid advancements in structure-based approaches, sequence-based methods remain significantly faster and more cost-effective. Her... read more 
bioinformatics

An explainable machine learning consensus framework for robust estimations of environmental effects on population dynamics

bioRxiv May 13, 2026
Explainable machine learning (ML) methods are gaining increasing attention in environmental and ecological research for their ability to reveal relationships between environmental drivers and population dynamics. However, there remain questions on th... read more 
ecology

MechAInistic: An LLM-guided Multi-Agent System for Reasoning over Genome-Scale Constraint-Based Metabolic Models

bioRxiv May 13, 2026
Constraint-based metabolic modeling is a powerful way to study the mechanistic basis of cellular states and disease, but its effective use demands substantial computational expertise and careful coordination of multi-step analyses. We developed MechA... read more 
systems biology
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