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

Innovations in Cancer Diagnostic and Decision Support (113) Natural Language Processing (924) Clinical Informatics (1339) Clinical Information and Decision Making (1938) Electronic Health Records (1331)

Published on in Vol 11 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/72005, first published .
Cancer Diagnosis Categorization in Electronic Health Records Using Large Language Models and BioBERT: Model Performance Evaluation Study

Cancer Diagnosis Categorization in Electronic Health Records Using Large Language Models and BioBERT: Model Performance Evaluation Study

Cancer Diagnosis Categorization in Electronic Health Records Using Large Language Models and BioBERT: Model Performance Evaluation Study

Authors of this article:

Soheil Hashtarkhani1 Author Orcid Image ;   Rezaur Rashid1 Author Orcid Image ;   Christopher L Brett2 Author Orcid Image ;   Lokesh Chinthala1 Author Orcid Image ;   Fekede Asefa Kumsa1 Author Orcid Image ;   Janet A Zink1 Author Orcid Image ;   Robert L Davis1 Author Orcid Image ;   David L Schwartz1, 3 Author Orcid Image ;   Arash Shaban-Nejad1 Author Orcid Image
Article Authors Cited by (2) Tweetations (1) Metrics

Journals

  1. Kumsa F, Brett C, Hashtarkhani S, Rashid R, Chinthala L, Zink J, Davis R, Shaban-Nejad A, Schwartz D. Leveraging Centralized Health System Data Management and Large Language Model–Based Data Preprocessing to Identify Predictors for Radiation Therapy Interruption. JCO Clinical Cancer Informatics 2025;(9) View
  2. May P, Greß J, Seidel C, Sommer S, Schuler M, Nokodian S, Schröder F, Jung J. Enabling Just-in-Time Clinical Oncology Analysis With Large Language Models: Feasibility and Validation Study Using Unstructured Synthetic Data. JMIR Medical Informatics 2025;13:e78332 View