V S Pakianathan, PavithrenFatehi, AlirezaSmeddinck, Jan2024-08-212024-08-212024https://dl.gi.de/handle/20.500.12116/44311Patient-generated health data has the potential to benefit health consultations; however, there are also challenges in implementing them into practice. A key challenge is to extract relevant data and allow for effective sensemaking to create actionability for both healthcare providers (HCPs) and patients. Based on a patient-journey model, we explore the use of generative AI to enable personalized data sensemaking to potentially improve shared decision-making between cardiovascular disease (CVD) patients and HCPs during the physical activity planning process in cardiovascular rehabilitation. We discuss open questions around interaction modalities, synchronicity, and patient-HCP social dynamics in the presence of conversational or agentic tools.enhttp://purl.org/eprint/accessRights/RestrictedAccessText/Workshop Paper10.18420/muc2024-mci-ws05-182