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The Collection of a Real-World, Large-Scale Dataset for Automated Skill Evaluation in Central Line Dressing Change

Paper recorded by Signals 4 on 2026-10-16 in cs.CV. Abstract reproduced from arXiv; link to the original below.

Published 2026-10-16 on arXiv · recorded by Signals 4 on 2026-10-19

Category: cs.CV · 计算机视觉 · first seen 2026-10-19

Abstract

Central line-associated bloodstream infections (CLABSIs) remain a major source of preventable morbidity and mortality in healthcare settings. Proper execution of the central line dressing change (CLDC) procedure is essential for infection prevention, yet current approaches to competency assessment rely primarily on manual ob- servation by clinical educators, making evaluation time-intensive, diffi

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#234 most recent of 756 cs.CV papers we have recorded · ↑ newer: Persistent Planar Memory for Video World Models · ↓ older: Video Diffusion Avatars: Taming Video Diffusion Models into Controllab
Cite this page: The Collection of a Real-World, Large-Scale Dataset for Automated Skill Evaluation in Central Line Dressing Change: the #234 most recent of 756 cs.CV papers we have recorded (as of 2026-10-16). Source: Signals 4 (Signals API) — https://data.jiangzhang.ca/signals4/t/papers/the-collection-of-a-real-world-large-scale-dataset-for-automated-skill-evaluatio.html
Free to quote with attribution to “Signals 4 (Signals API)”. Machine-readable: papers.json
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