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

Theme Issue 2021: Health Natural Language Processing and Applications (16) Ontologies, Classifications, and Coding (318) Natural Language Processing (893)

Published on in Vol 9, No 7 (2021): July

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/28218, first published .
Head and Tail Entity Fusion Model in Medical Knowledge Graph Construction: Case Study for Pituitary Adenoma

Head and Tail Entity Fusion Model in Medical Knowledge Graph Construction: Case Study for Pituitary Adenoma

Head and Tail Entity Fusion Model in Medical Knowledge Graph Construction: Case Study for Pituitary Adenoma

Authors of this article:

An Fang1, 2 Author Orcid Image ;   Pei Lou2 Author Orcid Image ;   Jiahui Hu2 Author Orcid Image ;   Wanqing Zhao2 Author Orcid Image ;   Ming Feng3 Author Orcid Image ;   Huiling Ren2 Author Orcid Image ;   Xianlai Chen4, 5 Author Orcid Image
Article Authors Cited by (4) Tweetations (2) Metrics

Journals

  1. Wu X, Duan J, Pan Y, Li M. Medical Knowledge Graph: Data Sources, Construction, Reasoning, and Applications. Big Data Mining and Analytics 2023;6(2):201 View
  2. Li J, Guo Z, He J, Ma X, Ma J. A Knowledge Graph Embedding Model Based on Cyclic Consistency—Cyclic_CKGE. Applied Sciences 2023;13(22):12380 View
  3. Wang R, Chen F, Chen H, Lin C, Shuai J, Wu Y, Ma L, Hu X, Wu M, Wang J, Zhao Q, Shuai J, Pan J. Deep Learning in Digital Breast Tomosynthesis: Current Status, Challenges, and Future Trends. MedComm 2025;6(6) View
  4. Hu J, Wang X, Yao K, Zhang X, Zhao W, Fu J, Lou P, Chen W, Fang A. FANS: A framework for automatic assessment of nutritional status based on free-text clinical notes. International Journal of Medical Informatics 2026;206:106168 View