Artificial Intelligence Medical Compendium

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

Showing 42,981 to 42,990 of 223,853 articles

SignalMC-MED: A Multimodal Benchmark for Evaluating Biosignal Foundation Models on Single-Lead ECG and PPG

arXiv Mar 10, 2026
Recent biosignal foundation models (FMs) have demonstrated promising performance across diverse clinical prediction tasks, yet systematic evaluation on long-duration multimodal data remains limited. We introduce SignalMC-MED, a benchmark for evaluati... read more 
Machine Learning

No Image, No Problem: End-to-End Multi-Task Cardiac Analysis from Undersampled k-Space

arXiv Mar 10, 2026
Conventional clinical CMR pipelines rely on a sequential "reconstruct-then-analyze" paradigm, forcing an ill-posed intermediate step that introduces avoidable artifacts and information bottlenecks. This creates a fundamental mathematical paradox: it ... read more 
Computer Vision and Pattern Recognition cs.AI

When Learning Rates Go Wrong: Early Structural Signals in PPO Actor-Critic

arXiv Mar 10, 2026
Deep Reinforcement Learning systems are highly sensitive to the learning rate (LR), and selecting stable and performant training runs often requires extensive hyperparameter search. In Proximal Policy Optimization (PPO) actor--critic methods, small L... read more 
Machine Learning cs.AI

Leveraging whole slide difficulty in Multiple Instance Learning to improve prostate cancer grading

arXiv Mar 10, 2026
Multiple Instance Learning (MIL) has been widely applied in histopathology to classify Whole Slide Images (WSIs) with slide-level diagnoses. While the ground truth is established by expert pathologists, the slides can be difficult to diagnose for non... read more 
Computer Vision and Pattern Recognition

From Semantics to Pixels: Coarse-to-Fine Masked Autoencoders for Hierarchical Visual Understanding

arXiv Mar 10, 2026
Self-supervised visual pre-training methods face an inherent tension: contrastive learning (CL) captures global semantics but loses fine-grained detail, while masked image modeling (MIM) preserves local textures but suffers from "attention drift" due... read more 
Computer Vision and Pattern Recognition cs.LG

BEACON: Language-Conditioned Navigation Affordance Prediction under Occlusion

arXiv Mar 10, 2026
Language-conditioned local navigation requires a robot to infer a nearby traversable target location from its current observation and an open-vocabulary, relational instruction. Existing vision-language spatial grounding methods usually rely on visio... read more 
Robotics cs.AI cs.CV

HTMuon: Improving Muon via Heavy-Tailed Spectral Correction

arXiv Mar 10, 2026
Muon has recently shown promising results in LLM training. In this work, we study how to further improve Muon. We argue that Muon's orthogonalized update rule suppresses the emergence of heavy-tailed weight spectra and over-emphasizes the training al... read more 
Machine Learning cs.AI

4DEquine: Disentangling Motion and Appearance for 4D Equine Reconstruction from Monocular Video

arXiv Mar 10, 2026
4D reconstruction of equine family (e.g. horses) from monocular video is important for animal welfare. Previous mainstream 4D animal reconstruction methods require joint optimization of motion and appearance over a whole video, which is time-consumin... read more 
Computer Vision and Pattern Recognition

HG-Lane: High-Fidelity Generation of Lane Scenes under Adverse Weather and Lighting Conditions without Re-annotation

arXiv Mar 10, 2026
Lane detection is a crucial task in autonomous driving, as it helps ensure the safe operation of vehicles. However, existing datasets such as CULane and TuSimple contain relatively limited data under extreme weather conditions, including rain, snow, ... read more 
Computer Vision and Pattern Recognition

Unbalanced Optimal Transport Dictionary Learning for Unsupervised Hyperspectral Image Clustering

arXiv Mar 10, 2026
Hyperspectral images capture vast amounts of high-dimensional spectral information about a scene, making labeling an intensive task that is resistant to out-of-the-box statistical methods. Unsupervised learning of clusters allows for automated segmen... read more 
Computer Vision and Pattern Recognition cs.LG math.ST
Popular Topics
Recent Journals