Work

A Two-Phase Visualization System for Continuous Human-AI Collaboration in Sequelae Analysis and Modeling

Year: 2024

Type: conference-paper

Abstract: 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 over-simplifies 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.

Source: IEEE Visualization and Visual Analytics (VIS)

DOI: 10.1109/vis55277.2024.00028

Authors: Yang Ouyang, Chenyang Zhang, He Wang, Tianle Ma, Chang Jiang, Yuheng Yan, Zuoqin Yan, Xiaojuan Ma, Chuhan Shi, Quan Li

Institutions: ShanghaiTech University, University of Illinois Urbana-Champaign, Zhongshan Hospital, Hong Kong University of Science and Technology, Southeast University

Language: English

Topic: Data Visualization and Analytics

Subfield: Computer Vision and Pattern Recognition

Field: Computer Science

Domain: Physical Sciences

SDG: Good health and well-being

Open Access status: green

OpenAlex ID: W4404915357

FWCI: 0.211

Cites: 35

Cited by: 1

Related to: 10