Artificial Intelligence Medical Compendium

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

Showing 58,191 to 58,200 of 227,634 articles

Analyzing Images of Blood Cells with Quantum Machine Learning Methods: Equilibrium Propagation and Variational Quantum Circuits to Detect Acute Myeloid Leukemia

arXiv Jan 26, 2026
This paper presents a feasibility study demonstrating that quantum machine learning (QML) algorithms achieve competitive performance on real-world medical imaging despite operating under severe constraints. We evaluate Equilibrium Propagation (EP), a... read more 
Emerging Technologies cs.LG quant-ph

Riemannian AmbientFlow: Towards Simultaneous Manifold Learning and Generative Modeling from Corrupted Data

arXiv Jan 26, 2026
Modern generative modeling methods have demonstrated strong performance in learning complex data distributions from clean samples. In many scientific and imaging applications, however, clean samples are unavailable, and only noisy or linearly corrupt... read more 
Machine Learning math.DG math.OC math.ST

SeNeDiF-OOD: Semantic Nested Dichotomy Fusion for Out-of-Distribution Detection Methodology in Open-World Classification. A Case Study on Monument Style Classification

arXiv Jan 26, 2026
Out-of-distribution (OOD) detection is a fundamental requirement for the reliable deployment of artificial intelligence applications in open-world environments. However, addressing the heterogeneous nature of OOD data, ranging from low-level corrupti... read more 
Computer Vision and Pattern Recognition cs.AI

HalluGuard: Demystifying Data-Driven and Reasoning-Driven Hallucinations in LLMs

arXiv Jan 26, 2026
The reliability of Large Language Models (LLMs) in high-stakes domains such as healthcare, law, and scientific discovery is often compromised by hallucinations. These failures typically stem from two sources: data-driven hallucinations and reasoning-... read more 
Machine Learning cs.AI

ctELM: Decoding and Manipulating Embeddings of Clinical Trials with Embedding Language Models

arXiv Jan 26, 2026
Text embeddings have become an essential part of a variety of language applications. However, methods for interpreting, exploring and reversing embedding spaces are limited, reducing transparency and precluding potentially valuable generative use cas... read more 
Computation and Language cs.AI cs.LG

Machine learning-driven nanoparticle-enhanced paper chromogenic array sensor approach for detecting sub-lethally injured Salmonella in low moisture food.

Food research international (Ottawa, Ont.) Jan 26, 2026
Detection of sub-lethally injured pathogens is critical for improving food safety, particularly given regulatory recommendations that microbiological method validation include 50-80% injured cells. In food matrices like low moisture foods (LMFs), inj... read more 

FusionPath: Gene fusion pathogenicity prediction using protein structural data and contextual protein embeddings

bioRxiv Jan 26, 2026
Accurate prediction of gene fusion pathogenicity is critical for understanding oncogenic mechanisms and advancing precision oncology. While existing computational methods provide valuable insights, their performance remains limited by incomplete inte... read more 
bioinformatics

Mechanistic Language Modeling and Oxygenated 3D Screening Reveal Berberine and Enzalutamide Synergy in Resistant Prostate Cancer

bioRxiv Jan 26, 2026
Resistance to androgen receptor inhibitors remains a primary challenge in prostate cancer treatment, yet identifying synergistic co-therapies is hindered by immense combinatorial search spaces and the limited interpretability of predictive computatio... read more 
bioengineering

Single-Cell Raman Profiling Enables Rapid Precision Phage Therapy Against Multidrug-Resistant Hypervirulent Klebsiella pneumoniae

bioRxiv Jan 26, 2026
Multidrug-resistant hypervirulent Klebsiella pneumoniae (MDR-hvKP) poses a severe global health threat. Phage therapy is a promising alternative, but requires precise matching of phage to the bacterial strain. Here, we present a proof-of-concept meth... read more 
microbiology

CoEVFold suite: user friendly pipelines to visually represent protein coevolution

bioRxiv Jan 26, 2026
Multiple sequence alignment (MSA) data underlies current principles in protein folding and protein-protein interaction prediction, from which large language models (LLMs) in tandem with protein datasets, can predict protein structure. However, what i... read more 
microbiology
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