Accessibility Settings
It is important to us that you have a smooth navigation experience on our website. To ensure this, you can set global settings for your view of the website here.
Animations
We use some animations on this website. If you find these annoying, you can switch them off here at any time.
A Human-AI Collaboration Approach for Designing Patient-Centered Technologies
Part of the HPI-MIT Designing for Sustainability Program, this project aims to develop and test a Human-AI collaboration approach that enhances text conversations in peer-to-peer support forums and supports a more dynamic elicitation of user needs.
Danielly de Paula
Prof. Dr. Ariel Stern (HPI - Chair for Digital Health, Economics, & Policy)
Prof. Dr. Marzyeh Ghassemi (MIT, Computer Science and Artificial Intelligence Lab - CSAIL)
September 2024 - August 2025
Despite the vast potential of digital health technologies, research indicates low user retention, which undermines the sustainability of these technologies. Digital sustainability emphasizes maintaining the effectiveness of digital solutions within evolving contexts. For digital health technologies to be sustainable, we need to implement mechanisms to continuously learn from patients, and use this data to continuously improve the application, keeping the solution relevant and effective. Accordingly, this proposal aims to develop and test an Artificial Intelligence (AI) agent that remains updated on patient experiences by analyzing and enhancing text conversations in peer-to-peer support forums and capturing user needs. The project intends to address the challenge of low user retention in digital health technologies and contribute to the fields of digital health sustainability, AI in healthcare, and human-centered design.
de Paula, D.; Juehling D., Uebernickel, F. (2024 - Forthcoming) Designing Digital Health Innovation for Stigma-Affected Health Conditions: A Systems-Based View to Managing Chronic Pelvic Pain. International Journal of Human-Computer Interaction.
de Paula, D., Sasso, A., Coester, J., & Boettinger, E. (2023). Core determinants of quality criteria for mHealth for hypertension: evidence from machine learning instruments. arXiv Preprint arXiv:2311.05434. https://doi.org/10.48550/arXiv.2311.05434
de Paula, D., Cormican, K., & Dobrigkeit, F. (2022). From Acquaintances to Partners in Innovation: An Analysis of 20 Years of Design Thinking’s Contribution to New Product Development. IEEE Transactions on Engineering Management, 69(4), 1664–1677. 10.1109/TEM.2021.3084884
