A multimodal approach using fundus images and text meta-data in a machine learning classifier with embeddings to predict years with self-reported diabetes - An exploratory analysis.

Journal: Primary care diabetes
PMID: 38616442

Abstract

AIMS: Machine learning models can use image and text data to predict the number of years since diabetes diagnosis; such model can be applied to new patients to predict, approximately, how long the new patient may have lived with diabetes unknowingly. We aimed to develop a model to predict self-reported diabetes duration.

Authors

  • Rodrigo M Carrillo-Larco
    CRONICAS Centre of Excellence in Chronic Diseases, Universidad Peruana Cayetano Heredia, Lima, Peru.
  • Gusseppe Bravo-Rocca
    Barcelona Supercomputing Center, Barcelona, Spain.
  • Manuel Castillo-Cara
    Universidad de Lima, Lima, Peru.
  • Xiaolin Xu
    Clinical Center for Eye Tumors, Capital Medical University, Beijing, 100730, China; Beijing Tongren Eye Center, Beijing Tongren Hospital, Capital Medical University, No. 1 Dongjiaominxiang Stree, Dongcheng District, Beijing, 100730, China; Beijing Key Laboratory of Intraocular Tumor Diagnosis and Treatment, Beijing 100730, China.
  • Antonio Bernabe-Ortiz
    Universidad Cientifica del Sur, Lima, Peru.

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