Artificial Intelligence Medical Compendium

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

Showing 64,561 to 64,570 of 231,605 articles

Detecting Batch Heterogeneity via Likelihood Clustering

arXiv Jan 14, 2026
Batch effects represent a major confounder in genomic diagnostics. In copy number variant (CNV) detection from NGS, many algorithms compare read depth between test samples and a reference sample, assuming they are process-matched. When this assumptio... read more 
Genomics cs.LG stat.ME stat.ML

Diffusion-Driven Deceptive Patches: Adversarial Manipulation and Forensic Detection in Facial Identity Verification

arXiv Jan 14, 2026
This work presents an end-to-end pipeline for generating, refining, and evaluating adversarial patches to compromise facial biometric systems, with applications in forensic analysis and security testing. We utilize FGSM to generate adversarial noise ... read more 
Computer Vision and Pattern Recognition cs.AI

QFed: Parameter-Compact Quantum-Classical Federated Learning

arXiv Jan 14, 2026
Organizations and enterprises across domains such as healthcare, finance, and scientific research are increasingly required to extract collective intelligence from distributed, siloed datasets while adhering to strict privacy, regulatory, and soverei... read more 
Machine Learning cs.AI cs.DC

LCF3D: A Robust and Real-Time Late-Cascade Fusion Framework for 3D Object Detection in Autonomous Driving

arXiv Jan 14, 2026
Accurately localizing 3D objects like pedestrians, cyclists, and other vehicles is essential in Autonomous Driving. To ensure high detection performance, Autonomous Vehicles complement RGB cameras with LiDAR sensors, but effectively combining these d... read more 
Computer Vision and Pattern Recognition cs.RO

Longitudinal effects ambient AI scribe use on documentation burden and financial productivity: A quasi-experimental study

medRxiv Jan 14, 2026
BackgroundArtificial intelligence (AI) scribes have the potential to reduce documentation burden. Previous studies have mostly relied on aggregated, vendor-provided (e.g., Epics Signal) outcome measures, potentially obfuscating the true effect of AI ... read more 
health informatics

Integrative Multi-Omics Analysis Reveals Novel Molecular Signatures, Disease Stratification and Therapeutic Opportunities in Primary Ciliary Dyskinesia: First AI-ML empowered platform towards precision medicine targeting human ciliopathies

medRxiv Jan 14, 2026
Primary ciliary dyskinesia (PCD) belongs to the group of rare genetic disorders that is extremely hard to diagnose and treat. Current diagnostic modalities detect only 70% of cases and are technically demanding. It necessitates novel computational ap... read more 
health informatics

Accelerating Inference in Genomic Foundation Models via Speculative Decoding

bioRxiv Jan 14, 2026
Genomic and protein foundation models (GFMs and PFMs) have demonstrated strong performance in learning the language of DNA and proteins, but their use in large-scale sequence generation is limited by the latency of autoregressive decoding. Because ev... read more 
genomics

Predictive coding narrows the gap between convolutional networks and human brain function in misspelled-word reading

bioRxiv Jan 14, 2026
Humans can readily recognize words even when they are misspelled, though with slower responses, demonstrating remarkable robustness in reading. The computational mechanisms underlying this combination of robustness and cost in reading remain unclear.... read more 
neuroscience

Acoustic remote sensing with deep learning enables non-invasive estimation of seabird nest density

bioRxiv Jan 14, 2026
Passive Acoustic Monitoring (PAM) has advanced ecological research by enabling non-invasive recordings of wildlife vocalizations that provide insight into species presence, behavior, and reproductive activity. This remote-sensing approach is particul... read more 
zoology

NEuRT: A Transformer-Based Model for Explainable Neuronal Activity Analysis

bioRxiv Jan 14, 2026
The study of neuronal activity is essential for understanding brain function and its alterations in neurodegenerative diseases. Advances in in vivo imaging have enabled real-time observation of neuronal dynamics, but classical statistical methods str... read more 
neuroscience
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