In healthcare, AI techniques are widely used for tasks like risk assessment and anomaly detection. Despite AI's potential as a valuable assistant, its role in complex medical data analysis often oversimplifies human-AI collaboration dynamics. To address this, we collaborated with a local hospital, engaging six physicians and one data scientist in a formative study. From this collaboration, we propose a framework integrating two-phase interactive visualization systems: one for Human-Led, AI-Assisted Retrospective Analysis and another for AI-Mediated, Human-Reviewed Iterative Modeling. This framework aims to enhance understanding and discussion around effective human-AI collaboration in healthcare.
@article{arxiv.2407.14769,
title = {A Two-Phase Visualization System for Continuous Human-AI Collaboration in Sequelae Analysis and Modeling},
author = {Yang Ouyang and Chenyang Zhang and He Wang and Tianle Ma and Chang Jiang and Yuheng Yan and Zuoqin Yan and Xiaojuan Ma and Chuhan Shi and Quan Li},
journal= {arXiv preprint arXiv:2407.14769},
year = {2024}
}