Artificial Intelligence Medical Compendium

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

Showing 17,301 to 17,310 of 213,726 articles

RadGenome-Anatomy: A Large-Scale Anatomy-Labeled Chest Radiograph Dataset via Physically Grounded Volumetric Projection

arXiv May 17, 2026
Anatomical structure labels for chest radiographs are essential for medical image segmentation and a broad range of downstream diagnostic tasks. However, annotating anatomy directly on 2D chest radiographs is labor-intensive and intrinsically ambiguo... read more 
Computer Vision and Pattern Recognition

Von Economo neurons enable reliable social skill acquisition in recurrent spiking neural networks: a computational account with clinical predictions

arXiv May 17, 2026
Von Economo neurons (VENs) are selectively lost in behavioural-variant frontotemporal dementia (bvFTD) and reduced in autism spectrum conditions (ASC), yet their computational role in social learning remains unexplained. We train a spiking neural net... read more 
Neurons and Cognition cs.NE

Radial-Angular Geometry for Reliable Update Diagnosis in Noisy-Label Learning

arXiv May 17, 2026
Noisy-label methods often estimate sample reliability from forward-space signals such as loss, confidence, or entropy. These signals indicate whether a sample is difficult to predict, but they do not directly test whether its observed label induces a... read more 
Machine Learning cs.CV

VISTA: Variance-Gated Inter-Sequence Test-Time Adaptation for Multi-Sequence MRI Segmentation

arXiv May 17, 2026
Deploying multi-sequence magnetic resonance imaging (MRI) segmentation models to new clinical environments is challenging due to variations in scanners and acquisition protocols. Although existing TTA methods handle basic per-modality shifts, they of... read more 
Computer Vision and Pattern Recognition

Medical Context Distorts Decisions in Clinical Vision Language Models

arXiv May 17, 2026
Vision-language models (VLMs) are increasingly proposed for clinical decision support, yet their reliability in real-world scenarios that require integrating both visual and textual context from medical records remains poorly characterized. This pape... read more 
Computer Vision and Pattern Recognition cs.CL

FastOCR: Dynamic Visual Fixation via KV Cache Pruning for Efficient Document Parsing

arXiv May 17, 2026
Vision-Language Models (VLMs) have shown strong promise on Optical Character Recognition (OCR), yet the sheer number of visual tokens required to encode dense documents incurs prohibitive inference cost. Existing pruning methods rely on physical evic... read more 
Computer Vision and Pattern Recognition cs.CL

Spatial Blindness in Whole-Slide Multiple Instance Learning

arXiv May 17, 2026
Whole-slide MIL models are often called context-aware once graphs, Transform ers, or state-space modules are placed above patch embeddings. We show that this label can be deceptive. On pathology tasks where tissue architecture is part of the diagnost... read more 
Computer Vision and Pattern Recognition cs.AI

GCE-MIL: Faithful and Recoverable Evidence for Multiple Instance Learning in Whole-Slide Imaging

arXiv May 17, 2026
Multiple instance learning (MIL) is the standard approach for whole-slide image (WSI) classification and survival prediction, where attention-based models ag gregate patch features into slide-level predictions. These models treat attention weights as... read more 
Computer Vision and Pattern Recognition cs.AI

EchoSR: Efficient Context Harnessing for Lightweight Image Super-Resolution

arXiv May 17, 2026
Image super-resolution (SR) aims to reconstruct high-quality, high-resolution (HR) images from low-resolution (LR) inputs and plays a critical role in various downstream applications. Despite recent advancements, balancing reconstruction fidelity and... read more 
Computer Vision and Pattern Recognition cs.MM eess.IV

On Applicability of Synthetic Datasets for Facial Expression Recognition

arXiv May 17, 2026
Facial Expression Recognition faces two core challenges. The first is class imbalance in public datasets, which skews the learning process and weakens generalization. The second is related to privacy and data collection constraints, which limit the s... read more 
Computer Vision and Pattern Recognition
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