Artificial Intelligence Medical Compendium

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

Showing 40,461 to 40,470 of 223,737 articles

Any-Subgroup Equivariant Networks via Symmetry Breaking

arXiv Mar 19, 2026
The inclusion of symmetries as an inductive bias, known as equivariance, often improves generalization on geometric data (e.g. grids, sets, and graphs). However, equivariant architectures are usually highly constrained, designed for symmetries chosen... read more 
Machine Learning

VeloxNet: Efficient Spatial Gating for Lightweight Embedded Image Classification

arXiv Mar 19, 2026
Deploying deep learning models on embedded devices for tasks such as aerial disaster monitoring and infrastructure inspection requires architectures that balance accuracy with strict constraints on model size, memory, and latency. This paper introduc... read more 
Computer Vision and Pattern Recognition

Vision Tiny Recursion Model (ViTRM): Parameter-Efficient Image Classification via Recursive State Refinement

arXiv Mar 19, 2026
The success of deep learning in computer vision has been driven by models of increasing scale, from deep Convolutional Neural Networks (CNN) to large Vision Transformers (ViT). While effective, these architectures are parameter-intensive and demand s... read more 
Computer Vision and Pattern Recognition

FedAgain: A Trust-Based and Robust Federated Learning Strategy for an Automated Kidney Stone Identification in Ureteroscopy

arXiv Mar 19, 2026
The reliability of artificial intelligence (AI) in medical imaging critically depends on its robustness to heterogeneous and corrupted images acquired with diverse devices across different hospitals which is highly challenging. Therefore, this paper ... read more 
Computer Vision and Pattern Recognition cs.AI

Gastric-X: A Multimodal Multi-Phase Benchmark Dataset for Advancing Vision-Language Models in Gastric Cancer Analysis

arXiv Mar 19, 2026
Recent vision-language models (VLMs) have shown strong generalization and multimodal reasoning abilities in natural domains. However, their application to medical diagnosis remains limited by the lack of comprehensive and structured datasets that cap... read more 
Computer Vision and Pattern Recognition cs.AI

ReXInTheWild: A Unified Benchmark for Medical Photograph Understanding

arXiv Mar 19, 2026
Everyday photographs taken with ordinary cameras are already widely used in telemedicine and other online health conversations, yet no comprehensive benchmark evaluates whether vision-language models can interpret their medical content. Analyzing the... read more 
Computer Vision and Pattern Recognition cs.LG

dinov3.seg: Open-Vocabulary Semantic Segmentation with DINOv3

arXiv Mar 19, 2026
Open-Vocabulary Semantic Segmentation (OVSS) assigns pixel-level labels from an open set of text-defined categories, demanding reliable generalization to unseen classes at inference. Although modern vision-language models (VLMs) support strong open-v... read more 
Computer Vision and Pattern Recognition cs.AI

The results of Transcriptome-wide Mendelian Randomization (TWMR) in large-scale populations can directly validate, across scales, the results of causal inference from deep learning combined with double machine learning on single-cell transcriptomes of human samples.

medRxiv Mar 19, 2026
Objective Aiming at the core problems prevalent in biomedical research, including the "translational distance", the difficulty in aligning cross-scale studies, and the lack of direct validation of single-cell systems biology models in human samples, ... read more 
rheumatology

HybridNet-XR: Efficient Teacher-Free Self-Supervised Learning for Autonomous Medical Diagnostic Systems in Resource-Constrained Environments.

medRxiv Mar 19, 2026
Deep learning model classification on large datasets is often limited in countries with restricted computational resources. While transfer learning can offset these limitations, standard architectures often maintain a high memory footprint. This stud... read more 
health informatics

Clinician Experiences with Ambient AI Scribe Technology in Singapore: A Qualitative Study

medRxiv Mar 19, 2026
Background: The administrative burden of clinical documentation is a recognised contributor to clinician burnout and diminished care quality. Ambient artificial intelligence (AI) scribe technology, which uses large language models to passively record... read more 
health informatics
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