Identifying clusters of people with Multiple Long-Term Conditions using Large Language Models: a population-based study

Identifying clusters of people with Multiple Long-Term Conditions using Large Language Models: a population-based study

Abstract Identifying clusters of people with similar patterns of Multiple Long-Term Conditions (MLTC) could help healthcare services to tailor care. In this population-based study, we developed a pipeline incorporating a DeBERTa language model to generate gender-specific clusters. Our model, EHR-DeB...

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Bibliographic Details
Main Authors: Alexander Smith, Thomas Beaney, Carinna Hockham, Bowen Su, Paul Elliott, Laura Downey, Spiros Denaxas, Payam Barnaghi, Abbas Dehghan, Ioanna Tzoulaki
Format: Article
Language:English
Published: Nature Portfolio 2025-07-01
Series:npj Digital Medicine
Online Access:https://doi.org/10.1038/s41746-025-01806-9
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