Published on in Vol 9, No 12 (2021): December

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/32698, first published .
A BERT-Based Generation Model to Transform Medical Texts to SQL Queries for Electronic Medical Records: Model Development and Validation

A BERT-Based Generation Model to Transform Medical Texts to SQL Queries for Electronic Medical Records: Model Development and Validation

A BERT-Based Generation Model to Transform Medical Texts to SQL Queries for Electronic Medical Records: Model Development and Validation

Journals

  1. Kesiku C, Chaves-Villota A, Garcia-Zapirain B. Natural Language Processing Techniques for Text Classification of Biomedical Documents: A Systematic Review. Information 2022;13(10):499 View
  2. Soni S, Datta S, Roberts K. quEHRy: a question answering system to query electronic health records. Journal of the American Medical Informatics Association 2023;30(6):1091 View
  3. Dobbins N, Han B, Zhou W, Lan K, Kim H, Harrington R, Uzuner Ö, Yetisgen M. LeafAI: query generator for clinical cohort discovery rivaling a human programmer. Journal of the American Medical Informatics Association 2023;30(12):1954 View
  4. Mo T, Xiao Q, Zhang H, Li R, Wu Y. Domain-Specific Few-Shot Table Prompt Question Answering via Contrastive Exemplar Selection. Algorithms 2024;17(7):278 View
  5. Marshan A, Almutairi A, Ioannou A, Bell D, Monaghan A, Arzoky M. MedT5SQL: a transformers-based large language model for text-to-SQL conversion in the healthcare domain. Frontiers in Big Data 2024;7 View