Published on in Vol 11, No 6 (2022): June

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/34405, first published .
Development and Validation of Population Clusters for Integrating Health and Social Care: Protocol for a Mixed Methods Study in Multiple Long-Term Conditions (Cluster-Artificial Intelligence for Multiple Long-Term Conditions)

Development and Validation of Population Clusters for Integrating Health and Social Care: Protocol for a Mixed Methods Study in Multiple Long-Term Conditions (Cluster-Artificial Intelligence for Multiple Long-Term Conditions)

Development and Validation of Population Clusters for Integrating Health and Social Care: Protocol for a Mixed Methods Study in Multiple Long-Term Conditions (Cluster-Artificial Intelligence for Multiple Long-Term Conditions)

Journals

  1. Holt S, Simpson G, Santer M, Everitt H, Farmer A, Zhou K, Qian Z, Davies F, Dambha-Miller H, Morrison L. Value of using artificial intelligence derived clusters by health and social care need in primary care: A qualitative interview study with patients living with multiple long-term conditions, carers and health care professionals. Journal of Multimorbidity and Comorbidity 2025;15 View
  2. Dambha-Miller H, Nagdi U, Smith L, Simpson G. Temperature extremes, climate change and multimorbidity: A rapid scoping review. The Journal of Climate Change and Health 2025;24:100452 View
  3. Dylag J, Zlatev Z, Boniface M. Pretrained language models for semantics-aware data harmonisation of observational clinical studies in the era of big data. BMC Medical Informatics and Decision Making 2025;25(1) View