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Large language multimodal models for new-onset type 2 diabetes prediction using five-year cohort ele...

Large language multimodal models for new-onset type 2 diabetes prediction using five-year cohort ele...

https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_b2ceacc8b2fc4af681bf63706937197d

Large language multimodal models for new-onset type 2 diabetes prediction using five-year cohort electronic health records

About this item

Full title

Large language multimodal models for new-onset type 2 diabetes prediction using five-year cohort electronic health records

Publisher

London: Nature Publishing Group UK

Journal title

Scientific reports, 2024-09, Vol.14 (1), p.20774-12, Article 20774

Language

English

Formats

Publication information

Publisher

London: Nature Publishing Group UK

More information

Scope and Contents

Contents

Type 2 diabetes mellitus (T2DM) is a prevalent health challenge faced by countries worldwide. In this study, we propose a novel large language multimodal models (LLMMs) framework incorporating multimodal data from clinical notes and laboratory results for diabetes risk prediction. We collected five years of electronic health records (EHRs) dating f...

Alternative Titles

Full title

Large language multimodal models for new-onset type 2 diabetes prediction using five-year cohort electronic health records

Identifiers

Primary Identifiers

Record Identifier

TN_cdi_doaj_primary_oai_doaj_org_article_b2ceacc8b2fc4af681bf63706937197d

Permalink

https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_b2ceacc8b2fc4af681bf63706937197d

Other Identifiers

ISSN

2045-2322

E-ISSN

2045-2322

DOI

10.1038/s41598-024-71020-2

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