Artificial Intelligence Medical Compendium

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

Showing 39,391 to 39,400 of 223,737 articles

Causal Reconstruction of Sentiment Signals from Sparse News Data

arXiv Mar 24, 2026
Sentiment signals derived from sparse news are commonly used in financial analysis and technology monitoring, yet transforming raw article-level observations into reliable temporal series remains a largely unsolved engineering problem. Rather than tr... read more 
Machine Learning stat.ML

PoiCGAN: A Targeted Poisoning Based on Feature-Label Joint Perturbation in Federated Learning

arXiv Mar 24, 2026
Federated Learning (FL), as a popular distributed learning paradigm, has shown outstanding performance in improving computational efficiency and protecting data privacy, and is widely applied in industrial image classification. However, due to its di... read more 
Machine Learning cs.AI

MetaKube: An Experience-Aware LLM Framework for Kubernetes Failure Diagnosis

arXiv Mar 24, 2026
Existing LLM-based Kubernetes diagnostic systems cannot learn from operational experience, operating on static knowledge bases without improving from past resolutions. We present MetaKube, an experience-aware LLM framework through three synergistic i... read more 
Machine Learning

AI Generalisation Gap In Comorbid Sleep Disorder Staging

arXiv Mar 24, 2026
Accurate sleep staging is essential for diagnosing OSA and hypopnea in stroke patients. Although PSG is reliable, it is costly, labor-intensive, and manually scored. While deep learning enables automated EEG-based sleep staging in healthy subjects, o... read more 
Machine Learning cs.AI

Ukrainian Visual Word Sense Disambiguation Benchmark

arXiv Mar 24, 2026
This study presents a benchmark for evaluating the Visual Word Sense Disambiguation (Visual-WSD) task in Ukrainian. The main goal of the Visual-WSD task is to identify, with minimal contextual information, the most appropriate representation of a giv... read more 
Computer Vision and Pattern Recognition cs.AI

λSplit: Self-Supervised Content-Aware Spectral Unmixing for Fluorescence Microscopy

arXiv Mar 24, 2026
In fluorescence microscopy, spectral unmixing aims to recover individual fluorophore concentrations from spectral images that capture mixed fluorophore emissions. Since classical methods operate pixel-wise and rely on least-squares fitting, their per... read more 
Computer Vision and Pattern Recognition cs.AI cs.LG

Boost Like a (Var)Pro: Trust-Region Gradient Boosting via Variable Projection

arXiv Mar 24, 2026
Gradient boosting, a method of building additive ensembles from weak learners, has established itself as a practical and theoretically-motivated approach to approximate functions, especially using decision tree weak learners. Comparable methods for s... read more 
Machine Learning math.NA math.OC

PerturbationDrive: A Framework for Perturbation-Based Testing of ADAS

arXiv Mar 24, 2026
Advanced driver assistance systems (ADAS) often rely on deep neural networks to interpret driving images and support vehicle control. Although reliable under nominal conditions, these systems remain vulnerable to input variations and out-of-distribut... read more 
Software Engineering

Estimating Individual Tree Height and Species from UAV Imagery

arXiv Mar 24, 2026
Accurate estimation of forest biomass, a major carbon sink, relies heavily on tree-level traits such as height and species. Unoccupied Aerial Vehicles (UAVs) capturing high-resolution imagery from a single RGB camera offer a cost-effective and scalab... read more 
Computer Vision and Pattern Recognition cs.AI cs.LG

Prototype Fusion: A Training-Free Multi-Layer Approach to OOD Detection

arXiv Mar 24, 2026
Deep learning models are increasingly deployed in safety-critical applications, where reliable out-of-distribution (OOD) detection is essential to ensure robustness. Existing methods predominantly rely on the penultimate-layer activations of neural n... read more 
Computer Vision and Pattern Recognition cs.AI
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