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Towards AI Augmented Personalized Data Sensemaking

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2024

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Gesellschaft für Informatik e.V.

Zusammenfassung

Patient-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.

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V S Pakianathan, Pavithren; Fatehi, Alireza; Smeddinck, Jan (2024): Towards AI Augmented Personalized Data Sensemaking. Mensch und Computer 2024 - Workshopband. DOI: 10.18420/muc2024-mci-ws05-182. Gesellschaft für Informatik e.V.. MCI-WS05: AI and Health: Using Digital Twins to Foster Healthy Behavior. Karlsruhe. 1.-4. September 2024

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