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

Clinical Information and Decision Making (1407) Electronic Health Records (1053) Machine Learning (1465) Natural Language Processing (692) Ontologies, Classifications, and Coding (239)

Published on in Vol 23, No 1 (2021): January

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/25113, first published .
Disease Concept-Embedding Based on the Self-Supervised Method for Medical Information Extraction from Electronic Health Records and Disease Retrieval: Algorithm Development and Validation Study

Disease Concept-Embedding Based on the Self-Supervised Method for Medical Information Extraction from Electronic Health Records and Disease Retrieval: Algorithm Development and Validation Study

Disease Concept-Embedding Based on the Self-Supervised Method for Medical Information Extraction from Electronic Health Records and Disease Retrieval: Algorithm Development and Validation Study

Authors of this article:

Yen-Pin Chen1, 2, 3 Author Orcid Image ;   Yuan-Hsun Lo4 Author Orcid Image ;   Feipei Lai1 Author Orcid Image ;   Chien-Hua Huang3 Author Orcid Image
Article Authors Cited by (15) Tweetations (4) Metrics

Journals

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  2. Chen Y, Huang C, Lo Y, Chen Y, Lai F. Combining attention with spectrum to handle missing values on time series data without imputation. Information Sciences 2022;609:1271 View
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  10. Siebra C, Kurpicz-Briki M, Wac K. Transformers in health: a systematic review on architectures for longitudinal data analysis. Artificial Intelligence Review 2024;57(2) View
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  12. Lee Y, Jeon S, Won J, Auh Q, Noh Y. Automatic detection and visualization of temporomandibular joint effusion with deep neural network. Scientific Reports 2024;14(1) View
  13. Li Y, Luan Z, Liu Y, Liu H, Qi J, Han D. Automated information extraction model enhancing traditional Chinese medicine RCT evidence extraction (Evi-BERT): algorithm development and validation. Frontiers in Artificial Intelligence 2024;7 View
  14. Nunes M, Bone J, Ferreira J, Elvas L. Health Care Language Models and Their Fine-Tuning for Information Extraction: Scoping Review. JMIR Medical Informatics 2024;12:e60164 View