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

Formative Evaluation of Digital Health Interventions (2410) Theme Issue 2022: Health Natural Language Processing and Applications (CHIP) (27) Decision Support for Health Professionals (1185) Machine Learning (1465) Natural Language Processing (692) Clinical Information and Decision Making (1407)

Published on in Vol 7 (2023)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/38125, first published .
How Natural Language Processing Can Aid With Pulmonary Oncology Tumor Node Metastasis Staging From Free-Text Radiology Reports: Algorithm Development and Validation

How Natural Language Processing Can Aid With Pulmonary Oncology Tumor Node Metastasis Staging From Free-Text Radiology Reports: Algorithm Development and Validation

How Natural Language Processing Can Aid With Pulmonary Oncology Tumor Node Metastasis Staging From Free-Text Radiology Reports: Algorithm Development and Validation

Authors of this article:

Sander Puts1, 2 Author Orcid Image ;   Martijn Nobel3, 4 Author Orcid Image ;   Catharina Zegers1, 2 Author Orcid Image ;   Iñigo Bermejo1 Author Orcid Image ;   Simon Robben3, 4 Author Orcid Image ;   Andre Dekker1, 2 Author Orcid Image
Article Authors Cited by (3) Tweetations (4) Metrics

Journals

  1. Nobel J, Puts S, Krdzalic J, Zegers K, Lobbes M, F. Robben S, Dekker A. Natural Language Processing Algorithm Used for Staging Pulmonary Oncology from Free-Text Radiological Reports: “Including PET-CT and Validation Towards Clinical Use”. Journal of Imaging Informatics in Medicine 2024;37(1):3 View
  2. Suzuki K, Yamada H, Yamazaki H, Honda G, Sakai S. Preliminary assessment of TNM classification performance for pancreatic cancer in Japanese radiology reports using GPT-4. Japanese Journal of Radiology 2024 View