This paper is in the following e-collection/theme issue:

Electronic Health Records (1053) Clinical Informatics (1022) Clinical Information and Decision Making (1407) eHealth Infrastructures (345) Secondary Use of Clinical Data for Research and Surveillance (367) Data Science (270) Advanced Data Analytics in eHealth (133) Natural Language Processing (692) Big Data (240) Ontologies, Classifications, and Coding (239)

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

Authors of this article:

Youcheng Pan1 Author Orcid Image ;   Chenghao Wang1 Author Orcid Image ;   Baotian Hu1 Author Orcid Image ;   Yang Xiang2 Author Orcid Image ;   Xiaolong Wang1 Author Orcid Image ;   Qingcai Chen1, 2 Author Orcid Image ;   Junjie Chen1 Author Orcid Image ;   Jingcheng Du3 Author Orcid Image
Article Authors Cited by (6) Tweetations (2) Metrics

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
  6. Bardhan J, Roberts K, Wang D. Question Answering for Electronic Health Records: Scoping Review of Datasets and Models. Journal of Medical Internet Research 2024;26:e53636 View