Human-AI Collaboration

First International Workshop, HAIC 2025, Held in Conjunction with MICCAI 2025, Daejeon, South Korea, September 27, 2025, Proceedings

Häftad, Engelska, 2025

Av Xiaoqing Guo, Yueming Jin, Hala Lamdouar, Qianhui Men, Cheng Ouyang, Manish Sahu, S. Swaroop Vedula

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This book constitutes the refereed proceedings of the First International Workshop, HAIC 2025, held in Conjunction with MICCAI 2025, Daejeon, South Korea, in September 27, 2025.The 9 full papers presented in this book were carefully selected and reviewed from 12 submissions. These papers have been organized in the following topical sections:Medical image computing; computer-assisted intervention; human-ai collaboration; human-computer interaction; human factor modeling; medical image analysis.

Produktinformation

Utgivningsdatum2025-10-30
Mått155 x 235 x 7 mm
Vikt189 g
FormatHäftad
SpråkEngelska
SerieLecture Notes in Computer Science
Antal sidor104
FörlagSpringer Nature Switzerland AG
ISBN9783032089694

Tillhör följande kategorier

.- Design and assessment for joint systems and workflows..- Beyond Manual Annotation: A Human-AI Collaborative Framework for Medical Image Segmentation Using Only “Better or Worse” Expert Feedback..- A methodology for clinically driven interactive segmentation evaluation..- Interactive environments for clinical training, education,and human-AI teaming..- Explainable AI for Automated User-specific Feedback in Surgical Skill Acquisition..- Real-Time, Dynamic, and Highly Generalizable Ultrasound Image Simulation-Guided Procedure Training System for Musculoskeletal Minimally Invasive Treatment..- Human-in-the-loop model training..- Learning What is Worth Learning: Active and Sequential Domain Adaptation for Multi-modal Gross Tumor Volume Segmentation..- Guided Active Learning for Medical Image Segmentation..- Applications of human-AI interaction, collaboration, and human factor analysis..- User Perception of Attention Visualizations: Effects on Interpretability Across Evidence-Based Medical Documents..- Simulating Inter-observer Variability Across Clinical Experience Levels..- Boosting transparency, interpretability, and risk management..- Perceptual Evaluation of GANs and Diffusion Models for Generating X-rays.