CardioAI: A Multimodal AI-based System to Support Symptom Monitoring and Risk Prediction of Cancer Treatment-Induced Cardiotoxicity

要旨

Despite recent advances in cancer treatments that prolong patients' lives, treatment-induced cardiotoxicity (i.e., the various heart damages caused by cancer treatments) emerges as one major side effect. The clinical decision-making process of cardiotoxicity is challenging, as early symptoms may happen in non-clinical settings and are too subtle to be noticed until life-threatening events occur at a later stage; clinicians already have a high workload focusing on the cancer treatment, no additional effort to spare on the cardiotoxicity side effect. Our project starts with a participatory design study with 11 clinicians to understand their decision-making practices and their feedback on an initial design of an AI-based decision-support system. Based on their feedback, we then propose a multimodal AI system, CardioAI, that can integrate wearables data and voice assistant data to model a patient's cardiotoxicity risk to support clinicians' decision-making. We conclude our paper with a small-scale heuristic evaluation with four experts and the discussion of future design considerations.

著者
Siyi Wu
University of Toronto, Toronto, Ontario, Canada
Weidan Cao
The Ohio State University, Columbus, Ohio, United States
Shihan Fu
Northeastern University, Boston, Massachusetts, United States
Bingsheng Yao
Northeastern University, Boston, Massachusetts, United States
Ziqi Yang
Northeastern University, Boston, Massachusetts, United States
Changchang Yin
The Ohio State University, Columbus, Ohio, United States
Varun Mishra
Northeastern University, Boston, Massachusetts, United States
Daniel Addison
Ohio State University, Columbus, Ohio, United States
Ping Zhang
The Ohio State University, Columbus, Ohio, United States
Dakuo Wang
Northeastern University, Boston, Massachusetts, United States
DOI

10.1145/3706598.3714272

論文URL

https://dl.acm.org/doi/10.1145/3706598.3714272

動画

会議: CHI 2025

The ACM CHI Conference on Human Factors in Computing Systems (https://chi2025.acm.org/)

セッション: Digital Health for Different User Needs

G314+G315
7 件の発表
2025-04-30 20:10:00
2025-04-30 21:40:00
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