Building a Human Digital Twin (HDTwin) Using Large Language Models for Cognitive Diagnosis: Algorithm Development and Validation
HDTwin integrates diverse cognitive health data, enhancing the accuracy and explainability of cognitive diagnoses. This approach outperforms traditional models and provides an interface for navigating patient information. The approach shows promise for improving early detection and intervention strategies in cognitive health.
Authors
- Diane J. Cook (ORCID: https://orcid.org/0000-0002-4441-7508)
- Gina Sprint (ORCID: https://orcid.org/0000-0001-9935-9950)
- Maureen Schmitter‐Edgecombe (ORCID: https://orcid.org/0000-0002-5304-2146)
Institutions
- Gonzaga University (US)
- Washington State University (US)
Publication Details
- Journal
- JMIR Formative Research
- Published
- 2024-11-07
- DOI
- https://doi.org/10.2196/63866
- Citations
- 3
- Primary Topic
- Artificial Intelligence in Healthcare and Education
- Type
- article
- Field-Weighted Citation Impact
- 0.36
Funders
- U.S. Department of Defense