This paper is in the following e-collection/theme issue:

Formative Evaluation of Digital Health Interventions (3207) AI Language Models in Health Care (198) Chatbots and Conversational Agents (739) Clinical Information and Decision Making (1908) Artificial Intelligence (2110) Research Instruments, Questionnaires, and Tools (736)

Published on in Vol 8 (2024)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/63866, first published .
Building a Human Digital Twin (HDTwin) Using Large Language Models for Cognitive Diagnosis: Algorithm Development and Validation

Building a Human Digital Twin (HDTwin) Using Large Language Models for Cognitive Diagnosis: Algorithm Development and Validation

Building a Human Digital Twin (HDTwin) Using Large Language Models for Cognitive Diagnosis: Algorithm Development and Validation

Authors of this article:

Gina Sprint1 Author Orcid Image ;   Maureen Schmitter-Edgecombe2 Author Orcid Image ;   Diane Cook2 Author Orcid Image
Article Authors Cited by (2) Tweetations Metrics

Journals

  1. Vallée A. Digital Twins for Personalized Medicine Require Epidemiological Data and Mathematical Modeling: Viewpoint. Journal of Medical Internet Research 2025;27:e72411 View
  2. Koksalmis G, Soykan B, Brattain L, Huang H. Statistical Learning for Personalized Prediction of Alzheimer's Disease Progression: A Survey of Methods, Data Challenges, and Future Directions. WIREs Computational Statistics 2025;17(3) View