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
Journals
- 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
- 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 2025;43(1):51 View
- Barlow S, Chicklore S, He Y, Ourselin S, Wagner T, Barnes A, Cook G. Uncertainty-aware automatic TNM staging classification for [18F] Fluorodeoxyglucose PET-CT reports for lung cancer utilising transformer-based language models and multi-task learning. BMC Medical Informatics and Decision Making 2024;24(1) View
- Chen Y, Zhang C, Bai R, Sun T, Ding W, Wang R. A review of medical text analysis: Theory and practice. Information Fusion 2025;119:103024 View
- Arends B, Vessies M, van Osch D, Teske A, van der Harst P, van Es R, van Es B. Diagnosis extraction from unstructured Dutch echocardiogram reports using span- and document-level characteristic classification. BMC Medical Informatics and Decision Making 2025;25(1) View