Published on in Vol 23, No 6 (2021): June

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/26892, first published .
Constructing High-Fidelity Phenotype Knowledge Graphs for Infectious Diseases With a Fine-Grained Semantic Information Model: Development and Usability Study

Constructing High-Fidelity Phenotype Knowledge Graphs for Infectious Diseases With a Fine-Grained Semantic Information Model: Development and Usability Study

Constructing High-Fidelity Phenotype Knowledge Graphs for Infectious Diseases With a Fine-Grained Semantic Information Model: Development and Usability Study

Journals

  1. Li S, Deng L, Zhang X, Chen L, Yang T, Qi Y, Jiang T. Deep Phenotyping of Chinese Electronic Health Records by Recognizing Linguistic Patterns of Phenotypic Narratives With a Sequence Motif Discovery Tool: Algorithm Development and Validation. Journal of Medical Internet Research 2022;24(6):e37213 View
  2. Deng L, Zhang X, Yang T, Liu M, Chen L, Jiang T. PIAT: An Evolutionarily Intelligent System for Deep Phenotyping of Chinese Electronic Health Records. IEEE Journal of Biomedical and Health Informatics 2022;26(8):4142 View
  3. Chen L, Qi Y, Wu A, Deng L, Jiang T. Mapping Chinese Medical Entities to the Unified Medical Language System. Health Data Science 2023;3 View
  4. Chen L, Qi Y, Wu A, Deng L, Jiang T. TeaBERT: An Efficient Knowledge Infused Cross-Lingual Language Model for Mapping Chinese Medical Entities to the Unified Medical Language System. IEEE Journal of Biomedical and Health Informatics 2023;27(12):6029 View