A Two-Phase Visualization System for Continuous Human-AI Collaboration in Sequelae Analysis and Modeling
<|reference_start|>A Two-Phase Visualization System for Continuous Human-AI Collaboration in Sequelae Analysis and Modeling: 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.<|reference_end|>
@article{ouyang2024a,
    title={A Two-Phase Visualization System for Continuous Human-AI Collaboration
  in Sequelae Analysis and Modeling},
    author={Yang Ouyang, Chenyang Zhang, He Wang, Tianle Ma, Chang Jiang, Yuheng
  Yan, Zuoqin Yan, Xiaojuan Ma, Chuhan Shi, and Quan Li},
    journal={arXiv preprint arXiv:2407.14769},
    year={2024},
    archivePrefix={arXiv},
    eprint={2407.14769},
    primaryClass={cs.HC}
}