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

Generative Language Models Including ChatGPT (757) Clinical Informatics (1377) Clinical Information and Decision Making (2004) Advanced Data Analytics in eHealth (222) New Methods (1153) Knowledge Translation and Implementation Science (545) Machine Learning (2166) Secondary Use of Clinical Data for Research and Surveillance (483)

Published on in Vol 27 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/65537, first published .
Large Language Model–Driven Knowledge Graph Construction in Sepsis Care Using Multicenter Clinical Databases: Development and Usability Study

Large Language Model–Driven Knowledge Graph Construction in Sepsis Care Using Multicenter Clinical Databases: Development and Usability Study

Large Language Model–Driven Knowledge Graph Construction in Sepsis Care Using Multicenter Clinical Databases: Development and Usability Study

Authors of this article:

Hao Yang1, 2, 3 Author Orcid Image ;   Jiaxi Li4 Author Orcid Image ;   Chi Zhang1 Author Orcid Image ;   Alejandro Pazos Sierra5 Author Orcid Image ;   Bairong Shen6 Author Orcid Image
Article Authors Cited by (14) Tweetations Metrics

Journals

  1. Zhang C, Yang H, Liu X, Wu R, Zong H, Wu E, Zhou Y, Li J, Shen B. A Knowledge-Enhanced Platform (MetaSepsisKnowHub) for Retrieval Augmented Generation–Based Sepsis Heterogeneity and Personalized Management: Development Study. Journal of Medical Internet Research 2025;27:e67201 View
  2. Kumar A, Singh D, Cypko M, Amft O. A multi-view validation framework for LLM-generated knowledge graphs of chronic kidney disease. International Journal of Computer Assisted Radiology and Surgery 2025;20(12):2523 View
  3. Xu Y, Long Z, Setyohadi D. Enhancing Diabetes Management With CRIBC: A Novel NER Model for Constructing A Comprehensive Chinese Medical Knowledge Graph. Engineering Reports 2025;7(10) View
  4. Rohanian M, Mehra T, Miglino N, Nooralahzadeh F, Krauthammer M, Wicki A. Towards scalable and cross-lingual specialist language models for oncology. Scientific Reports 2025;15(1) View
  5. Zhang W, Chen Y, Liu X, Zhang H. A large language model-based approach to building the knowledge graph for master plan: A case study in Guangzhou, China. Land Use Policy 2025;159:107807 View
  6. Shen B, Greig N, Kamal M. Translational Informatics for Neuropharmacology: Databases, Ontologies, and Analytics. Current Neuropharmacology 2025;23(14):1813 View
  7. Shi T, Ma J, Yu Z, Xu H, Yang R, Xiong M, Xiao M, Li Y, Zhao H, Kong G. Large Language Models in Critical Care Medicine: Scoping Review. JMIR Medical Informatics 2025;13:e76326 View
  8. Wang J, Zong H, Zhang Y, Liu X, Shen K, Li X, Wu R, Jiang M, Cebrián D, Dopico J, Shen B. CirRFKB: A knowledgebase of circadian-related risk factors for cancer pathogenesis and personalized medicine. Computational and Structural Biotechnology Journal 2025;27:5326 View
  9. Peng D, Phongpreecha T, Aghaeepour N. Artificial intelligence-guided nutritional therapy in the ICU. Current Opinion in Clinical Nutrition & Metabolic Care 2026;29(2):193 View
  10. AbuHaweeleh M, Chowdhury A, Newaz M, Saha P, Islam K, Kumar J, Chowdhury M, Pedersen S. Sepsis mortality prediction using machine learning and deep learning - a systematic review. BMC Medical Informatics and Decision Making 2025;26(1) View
  11. Zheng X, Bi C, Bo W, Zhang Y, Song J, Du J, Hu S, Feng J, Yang L, Shen B. DRPMKB1.0: A Comprehensive Knowledge Base for an AI-Oriented Drug Repositioning Prediction Model. Journal of Chemical Information and Modeling 2026;66(1):122 View

Books/Policy Documents

  1. Prathaban K, Akram F, Klein S, Starmans M. Emerging LLM/LMM Applications in Medical Imaging. View

Conference Proceedings

  1. Yadav A, Khan A, Hisham M, Kumari N, Kumar A, Sachdeva S. 2025 Seventeenth International Conference on Contemporary Computing (IC3). QueryViz: Visual Query Interface for Standardized Electronic Health Records View
  2. Nguyen T, You E, Kim H, Hoang V, Nguyen L, Lee O. Proceedings of the International Conference on Research in Adaptive and Convergent Systems. Constructing a Companion Animal Disease Knowledge Graph by Utilizing LLMs in Data Preprocessing and Pseudo Annotation View