Artificial Intelligence Medical Compendium

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

Showing 32,781 to 32,790 of 221,227 articles

Fine-Grained Action Segmentation for Renorrhaphy in Robot-Assisted Partial Nephrectomy

arXiv Apr 10, 2026
Fine-grained action segmentation during renorrhaphy in robot-assisted partial nephrectomy requires frame-level recognition of visually similar suturing gestures with variable duration and substantial class imbalance. The SIA-RAPN benchmark defines th... read more 
Computer Vision and Pattern Recognition cs.RO

Learning Vision-Language-Action World Models for Autonomous Driving

arXiv Apr 10, 2026
Vision-Language-Action (VLA) models have recently achieved notable progress in end-to-end autonomous driving by integrating perception, reasoning, and control within a unified multimodal framework. However, they often lack explicit modeling of tempor... read more 
Computer Vision and Pattern Recognition cs.AI

Nested Radially Monotone Polar Occupancy Estimation: Clinically-Grounded Optic Disc and Cup Segmentation for Glaucoma Screening

arXiv Apr 10, 2026
Valid segmentation of the optic disc (OD) and optic cup (OC) from fundus photographs is essential for glaucoma screening. Unfortunately, existing deep learning methods do not guarantee clinical validness including star-convexity and nested structure ... read more 
Computer Vision and Pattern Recognition

Cross-Modal Knowledge Distillation from Spatial Transcriptomics to Histology

arXiv Apr 10, 2026
Spatial transcriptomics provides a molecularly rich description of tissue organization, enabling unsupervised discovery of tissue niches -- spatially coherent regions of distinct cell-type composition and function that are relevant to both biological... read more 
Computer Vision and Pattern Recognition

Off-the-shelf Vision Models Benefit Image Manipulation Localization

arXiv Apr 10, 2026
Image manipulation localization (IML) and general vision tasks are typically treated as two separate research directions due to the fundamental differences between manipulation-specific and semantic features. In this paper, however, we bridge this ga... read more 
Computer Vision and Pattern Recognition cs.MM eess.IV

Physically Grounded 3D Generative Reconstruction under Hand Occlusion using Proprioception and Multi-Contact Touch

arXiv Apr 10, 2026
We propose a multimodal, physically grounded approach for metric-scale amodal object reconstruction and pose estimation under severe hand occlusion. Unlike prior occlusion-aware 3D generation methods that rely only on vision, we leverage physical int... read more 
Computer Vision and Pattern Recognition cs.RO

CLIP-Inspector: Model-Level Backdoor Detection for Prompt-Tuned CLIP via OOD Trigger Inversion

arXiv Apr 10, 2026
Organisations with limited data and computational resources increasingly outsource model training to Machine Learning as a Service (MLaaS) providers, who adapt vision-language models (VLMs) such as CLIP to downstream tasks via prompt tuning rather th... read more 
Cryptography and Security cs.AI cs.CV cs.LG

Detecting Diffusion-generated Images via Dynamic Assembly ForestsDetecting Diffusion-generated Images via Dynamic Assembly Forests

arXiv Apr 10, 2026
Diffusion models are known for generating high-quality images, causing serious security concerns. To combat this, most efforts rely on deep neural networks (e.g., CNNs and Transformers), while largely overlooking the potential of traditional machine ... read more 
Computer Vision and Pattern Recognition cs.LG

FIRE-CIR: Fine-grained Reasoning for Composed Fashion Image Retrieval

arXiv Apr 10, 2026
Composed image retrieval (CIR) aims to retrieve a target image that depicts a reference image modified by a textual description. While recent vision-language models (VLMs) achieve promising CIR performance by embedding images and text into a shared s... read more 
Computer Vision and Pattern Recognition cs.LG

Few-Shot Personalized Age Estimation

arXiv Apr 10, 2026
Existing age estimation methods treat each face as an independent sample, learning a global mapping from appearance to age. This ignores a well-documented phenomenon: individuals age at different rates due to genetics, lifestyle, and health, making t... read more 
Computer Vision and Pattern Recognition
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