Artificial Intelligence Medical Compendium

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

Showing 40,551 to 40,560 of 223,737 articles

Unrolled Reconstruction with Integrated Super-Resolution for Accelerated 3D LGE MRI

arXiv Mar 18, 2026
Accelerated 3D late gadolinium enhancement (LGE) MRI requires robust reconstruction methods to recover thin atrial structures from undersampled k-space data. While unrolled model-based networks effectively integrate physics-driven data consistency wi... read more 
Computer Vision and Pattern Recognition

VISTA: Validation-Guided Integration of Spatial and Temporal Foundation Models with Anatomical Decoding for Rare-Pathology VCE Event Detection

arXiv Mar 18, 2026
Capsule endoscopy event detection is challenging because diagnostically relevant findings are sparse, visually heterogeneous, and embedded in long, noisy video streams, while evaluation is performed at the event level rather than by frame accuracy al... read more 
Computer Vision and Pattern Recognition

Epistemic Generative Adversarial Networks

arXiv Mar 18, 2026
Generative models, particularly Generative Adversarial Networks (GANs), often suffer from a lack of output diversity, frequently generating similar samples rather than a wide range of variations. This paper introduces a novel generalization of the GA... read more 
Machine Learning cs.CV

From Drop-off to Recovery: A Mechanistic Analysis of Segmentation in MLLMs

arXiv Mar 18, 2026
Multimodal Large Language Models (MLLMs) are increasingly applied to pixel-level vision tasks, yet their intrinsic capacity for spatial understanding remains poorly understood. We investigate segmentation capacity through a layerwise linear probing e... read more 
Computer Vision and Pattern Recognition cs.AI cs.LG

Neural Radiance Maps for Extraterrestrial Navigation and Path Planning

arXiv Mar 18, 2026
Autonomous vehicles such as the Mars rovers currently lead the vanguard of surface exploration on extraterrestrial planets and moons. In order to accelerate the pace of exploration and science objectives, it is critical to plan safe and efficient pat... read more 
Robotics cs.CV

On the Cone Effect and Modality Gap in Medical Vision-Language Embeddings

arXiv Mar 18, 2026
Vision-Language Models (VLMs) exhibit a characteristic "cone effect" in which nonlinear encoders map embeddings into highly concentrated regions of the representation space, contributing to cross-modal separation known as the modality gap. While this... read more 
Machine Learning

Pathology-Aware Multi-View Contrastive Learning for Patient-Independent ECG Reconstruction

arXiv Mar 18, 2026
Reconstructing a 12-lead electrocardiogram (ECG) from a reduced lead set is an ill-posed inverse problem due to anatomical variability. Standard deep learning methods often ignore underlying cardiac pathology losing vital morphology in precordial lea... read more 
Machine Learning cs.AI

ConfusionBench: An Expert-Validated Benchmark for Confusion Recognition and Localization in Educational Videos

arXiv Mar 18, 2026
Recognizing and localizing student confusion from video is an important yet challenging problem in educational AI. Existing confusion datasets suffer from noisy labels, coarse temporal annotations, and limited expert validation, which hinder reliable... read more 
Computer Vision and Pattern Recognition

DANCE: Dynamic 3D CNN Pruning: Joint Frame, Channel, and Feature Adaptation for Energy Efficiency on the Edge

arXiv Mar 18, 2026
Modern convolutional neural networks (CNNs) are workhorses for video and image processing, but fail to adapt to the computational complexity of input samples in a dynamic manner to minimize energy consumption. In this research, we propose DANCE, a fi... read more 
Computer Vision and Pattern Recognition cs.AI

Classifier Pooling for Modern Ordinal Classification

arXiv Mar 18, 2026
Ordinal data is widely prevalent in clinical and other domains, yet there is a lack of both modern, machine-learning based methods and publicly available software to address it. In this paper, we present a model-agnostic method of ordinal classificat... read more 
Machine Learning stat.ME
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