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Digital symptom monitoring and activity tracking in chemoradiation-lessons from the CAM experience
J Fu1, A Pepin1, C Hollawell1
1Department of Radiation Oncology, University of Pennsylvania, Philadelphia, USA.
Abstract:
Artificial intelligence (AI) is increasingly being explored as a way to improve supportive care during chemoradiotherapy (CRT). Through our CAM 1.0 and CAM 2.0 studies, we examined how AI-supported remote patient monitoring could be integrated into CRT care, revealing both its potential benefits and its challenges in real-world implementation. We observed how AI can facilitate remote patient monitoring beyond routine visits, yet also how it may create additional tasks for providers, magnify digital inequities, and leave patients still seeking human connection. These experiences underscore that AI's impact in oncology will be defined not only by its technical capabilities but by how it fits into workflows, addresses barriers to access, and preserves the relational aspects of care. This perspectives piece aims to highlight the practical insights from CAM 1.0 and 2.0 that may inform how oncologists, developers, and health systems approach future AI integration into oncology workflows, particularly in the context of CRT. NCT: NCT05318027.
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