A novel data-driven approach for Personas validation in healthcare using self-supervised machine learning
The proposed method showed high capabilities in generalization beyond the training data, validating the Personas' capability of stratifying the characteristics of target populations. Additionally, this method significantly reduced the costs to validate Personas when compared to other methods in current literature.
Authors
- Enrico G. Caiani (ORCID: https://orcid.org/0000-0002-1770-6486)
- Grzegorz Bilo (ORCID: https://orcid.org/0000-0002-5104-9176)
- Alessandra Gorini (ORCID: https://orcid.org/0000-0003-3216-1784)
- Emanuele Tauro (ORCID: https://orcid.org/0000-0003-4307-2461)
Institutions
- Istituti Clinici Scientifici Maugeri (IT)
- IRCCS Istituto Auxologico Italiano (IT)
- Politecnico di Milano (IT)
Publication Details
- Journal
- Journal of Biomedical Informatics
- Published
- 2025-03-15
- DOI
- https://doi.org/10.1016/j.jbi.2025.104815
- Citations
- 1
- Primary Topic
- Persona Design and Applications
- Type
- article
- Field-Weighted Citation Impact
- 1.94
Funders
- Ministero della Salute