A Two-Phase Visualization System for Continuous Human-AI Collaboration in Sequelae Analysis and Modeling
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arXiv
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| Autores principales: | , , , , , , , , , |
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| Formato: | Preprint |
| Publicado: |
2024
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| Materias: | |
| Acceso en línea: | |
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| _version_ | 1866929429003894784 |
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| author | Ouyang, Yang Zhang, Chenyang Wang, He Ma, Tianle Jiang, Chang Yan, Yuheng Yan, Zuoqin Ma, Xiaojuan Shi, Chuhan Li, Quan |
| author_facet | Ouyang, Yang Zhang, Chenyang Wang, He Ma, Tianle Jiang, Chang Yan, Yuheng Yan, Zuoqin Ma, Xiaojuan Shi, Chuhan Li, Quan |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2407_14769 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | A Two-Phase Visualization System for Continuous Human-AI Collaboration in Sequelae Analysis and Modeling Ouyang, Yang Zhang, Chenyang Wang, He Ma, Tianle Jiang, Chang Yan, Yuheng Yan, Zuoqin Ma, Xiaojuan Shi, Chuhan Li, Quan Human-Computer Interaction 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. |
| title | A Two-Phase Visualization System for Continuous Human-AI Collaboration in Sequelae Analysis and Modeling |
| topic | Human-Computer Interaction |
| url | https://arxiv.org/abs/2407.14769 |