Artificial Intelligence Medical Compendium

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

Showing 5,151 to 5,160 of 204,028 articles

DMPKformer: An Interpretable Multimodal Deep Learning Framework for Reliable ADMET Property Prediction

bioRxiv May 29, 2026
Accurate prediction of absorption, distribution, metabolism, excretion, and toxicity (ADMET) properties remains a critical challenge in drug discovery. Traditional single modality approaches often fail to capture the complex, multi-scale relationship... read more 
bioinformatics

SortIT - A Tool For Assessing Observer Variability And Creating Ground Truth Image Classification Datasets

bioRxiv May 29, 2026
Interobserver variability in pathological assessments is a well-recognized challenge that impacts diagnostic reliability and disease understanding. This variability exists across many subspecialties due to the subjective nature of evaluations. Artifi... read more 
pathology

13C flux ratio analysis with FRAPPPE reveals differences in metabolic fluxes between gut Bacteroidota and Escherichia coli

bioRxiv May 29, 2026
Gut bacteria shape the metabolism of their host and play an important role in human health. However, systems biology approaches to study their intracellular metabolic fluxes are largely underdeveloped. We present an experimental and computational wor... read more 
microbiology

DINMC: A Deep Learning Framework for Interpretable Normative Model Construction and Pathological Brain Alteration Detection

bioRxiv May 29, 2026
Background and Objective: Normative modeling is a key tool for understanding brain alterations in neurodegenerative diseases, such as cerebellar-type multiple system atrophy. However, existing methods lack interpretability and fail to capture clinica... read more 
bioinformatics

Bimodal masked language modeling for bulk RNA-seq and DNA methylation representation learning

bioRxiv May 29, 2026
Oncologists are increasingly relying on multiple modalities to model the complexity of diseases. Within this landscape, transcriptomic and epigenetic data have proven to be particularly instrumental and play an increasingly vital role in clinical app... read more 
bioinformatics

Deconvolution improves cryo-EM maps

bioRxiv May 29, 2026
With technological advancements in recent years, single particle cryogenic electron microscopy (cryo-EM) has become a major methodology for structural biology. Structure determination by single particle cryo-EM is premised on randomly orientated part... read more 
biophysics

A voltage-controlled reconfigurable memristor with dual-mode synaptic plasticity for adaptive neuromorphic computing and mechanism analysis.

Nanotechnology May 29, 2026
In this study, we propose and experimentally validate a simple planar-integrated dual-device memristor structure based on HfO2/Al2O3heterostructure, which demonstrates voltage-modulated switching behavior between analog and digital resistance switch ... read more 

Machine learning models based on magnetic resonance imaging for predicting Lymphovascular Invasion in Invasive Breast Cancer.

PloS one May 29, 2026
OBJECTIVES: Treatment strategies for invasive breast cancer require accurate lymphovascular invasion (LVI) predictions. This study aimed to investigate the feasibility and effectiveness of delta radiomics signature based on dynamic contrast-enhanced ... read more 

A prototype-augmented graph representation learning framework for identifying brain disorder-associated genes and facilitating drug repurposing.

PLoS computational biology May 29, 2026
Many genetic loci were identified as associated with neuropsychiatric disorders and neurodegenerative disorders by Genome-wide association studies (GWAS). How these loci impact these diseases is unclear. Advances in deep-learning approaches and multi... read more 

TransGrid-CostOpt: A hybrid transformer framework for cost prediction and optimization of distribution network assets.

PloS one May 29, 2026
The prediction and optimization of distribution network asset costs is a complex problem in the power industry, involving the optimization of multiple objectives and the response to dynamic demands. Traditional methods often struggle to effectively a... read more 
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