Artificial Intelligence Medical Compendium

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

Showing 17,211 to 17,220 of 213,726 articles

Evaluating open LLMs for agentic analysis orchestration in a typical biomedical lab

bioRxiv May 18, 2026
Agentic tools - software environments where a large language model plans, calls external tools, executes code, and iterates with minimal human intervention - will run a substantial share of routine biomedical data analysis within the next few years. ... read more 
bioinformatics

Interpretable Predictive Modeling for Medical Data Using Boolean Rule-aware Regression

bioRxiv May 18, 2026
Purpose: In clinical practice, accurate prediction of disease risk must be accompanied by transparent, human-understandable explanations to support diagnostic confidence, guide therapeutic decisions, and meet ethical and regulatory standards. While d... read more 
bioinformatics

NeuroPupil: A generalization-first framework for scalable and biologically informative cross-species pupillometry

bioRxiv May 18, 2026
Quantitative pupillometry provides a noninvasive window into brain state and neurological function, but its broader use across experimental and clinical settings is limited by challenges in achieving accurate, scalable, and generalizable measurements... read more 
neuroscience

Estimating Daily Taxon-specific Tree Pollen at a 1-km Resolution in Atlanta, GA from 2020 to 2024

bioRxiv May 18, 2026
While tree pollen is a major trigger of allergic respiratory conditions and different taxa exhibit varying allergenic potentials, the lack of high-resolution, taxon-specific exposure metrics have limited our ability to identify which local pollen tax... read more 
plant biology

Stereochemistry-Aware Drug-Target Affinity Prediction

bioRxiv May 18, 2026
Drug-target affinity (DTA) prediction is a key task in drug discovery, enabling the estimation of the interaction strength between candidate compounds and biological targets. However, current models rely on connectivity-based molecular representation... read more 
bioinformatics

Learning Chirality-Aware Representations to Predict Drug Side Effect Frequencies

bioRxiv May 18, 2026
Ab initio prediction of side effect frequencies is important for assessing the risk-benefit profile of drugs and for identifying potential adverse effects early in development. A key challenge is chirality: many drugs exist as enantiomers, pairs of m... read more 
bioinformatics

A Multimodal Neural Network Model for Early Recurrence Prediction in Lung Adenocarcinoma

bioRxiv May 18, 2026
Lung adenocarcinoma (LUAD), a subtype of non-small cell lung cancer (NSCLC), is the most common primary lung cancer worldwide. Despite advancements in early detection and treatment, up to 39% of patients develop recurrent tumors following complete re... read more 
bioinformatics

DamageFormer: a damage-aware multimodal deep learning framework for DNA lesion identification from nanopore sequencing

bioRxiv May 18, 2026
Background: DNA lesions arise from endogenous metabolism and environmental exposure and are the major drivers of mutagenesis, aging, and cancer development. However, mapping DNA damage at nucleotide resolution remains a technically challenging task. ... read more 
genomics

Deep analysis of FANTOM CAGE data reveals hierarchical patterns of TSS co-deployment hubs and their disruption in cancers

bioRxiv May 18, 2026
Selective deployment of multiple transcription start sites is a major regulatory feature of human transcriptomes. FANTOM CAGE data exhibit a near-universal TSS deployment parsimony which is disrupted in cancers. We have recently shown that TSS deploy... read more 
genomics

FlexENN: A Graph Neural Network for Binding Energy Prediction of Globular and Intrinsically Disordered Proteins

bioRxiv May 18, 2026
Intrinsically disordered proteins (IDPs) drive a large fraction of cellular signaling, transcription and assembly through interfaces that lack a single defined geometry, making the prediction of their binding energies beyond the reach of methods cali... read more 
biophysics
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