Artificial Intelligence Medical Compendium

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

Showing 57,691 to 57,700 of 227,388 articles

PIMO: Pathway-based Interpretable Multi-Omics interactions for multi-omics integration

bioRxiv Jan 28, 2026
Motivation: Modeling inter-omics interactions across multiple molecular levels is critical for deciphering the mechanisms underlying complex diseases. Epigenomic and structural alterations, such as DNA methylation and copy number alterations, modulat... read more 
bioinformatics

Semantic axes in the brain support analogical representations

bioRxiv Jan 28, 2026
In vectorial embeddings of word meaning, semantic features often reflect consistent directions, or axes, within a representational space. A classic example is gender: the vector spanning boy to girl can be added to the embedding for king to predict q... read more 
neuroscience

Does charging for corrections in the bioscience literature disincentivize pre-publication handling of problematic image data? An ImageTwin-AI study.

bioRxiv Jan 28, 2026
The Committee on Publication Ethics (COPE) recommends that publishers do not charge for corrections to published papers. Until late 2024 the Journal of Cancer levied a charge on authors (50% of the original article processing charge, APC) for publica... read more 
cancer biology

Feature Integration of FDG PET Brain Imaging Using Deep Learning for Sensitive Cognitive Decline Detection

medRxiv Jan 28, 2026
Background Distinguishing individuals with cognitive decline (CD), including early Alzheimers disease, from cognitively normal (CN) individuals is essential for improving diagnostic accuracy and enabling timely intervention. Positron emission tomogra... read more 
neurology

Decoupling Accuracy and Explainability: Machine Learning Strategies for HbA1c Prediction and Biomarker Discovery in Blood FTIR Spectroscopy

medRxiv Jan 28, 2026
Glycated hemoglobin (HbA1c) is a central biomarker for long-term glycemic control and diabetes management, traditionally quantified using laboratory-intensive chromatographic or immunochemical assays. As the global burden of diabetes continues to ris... read more 
health informatics

Early Detection and Prediction of Emerging and Re-emerging Infectious Diseases using Data-driven Modelling: A focus on the 2022-2024 Global Monkeypox Viral Outbreak

medRxiv Jan 28, 2026
Monkeypox viral disease has been and continues to be a global public health concern. Currently, there are existing, though minimal measures to manage mpox and any future outbreaks. Relying on data-driven modeling for early detection of mpox and predi... read more 
epidemiology

Evaluating Spiking and Non-Spiking Neural Networks for Colorectal Serrated Polyp Subtype Classification

medRxiv Jan 27, 2026
Image classification on digital pathology images relies heavily on convolutional neural networks (CNNs), yet the behavior of alternative neural computing paragigms in this domain remains insufficiently characterized. Spiking neural networks (SNNs), w... read more 
pathology

Foundation Model Robustness to Technical Acquisition Parameters in Chest X-Ray AI A Multi-Architecture Comparative Study with External Validation

medRxiv Jan 27, 2026
Background Foundation models have emerged as a promising paradigm for medical imaging AI [7], with claims of improved generalization and reduced bias. However, their robustness to technical acquisition parameters remains unexplored. We evaluated whet... read more 
radiology and imaging

An Implantable Device that Converses with Patients and Learns to Co-Manage Epilepsy

medRxiv Jan 27, 2026
One-third of the world's 70 million people with epilepsy have seizures that are not controlled by medication; and implantable devices are an exciting option for treatment. These devices improve seizure control and can detect impending attacks, missed... read more 
neurology

Why Large Language Models' Clinical Reasoning Fails: Insights from Explainable Deep Learning

medRxiv Jan 27, 2026
BACKGROUND Medical large language models (LLMs) achieving high benchmark accuracy exhibit unexplained variability in clinical tasks, producing errors that clinicians cannot safeguard against. Sparse autoencoders offer a mechanistic interpretability a... read more 
health informatics
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