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

Theme Issue 2021: Health Natural Language Processing and Applications (16) Natural Language Processing (692) Machine Learning (1465) Decision Support for Health Professionals (1185) Lung Cancer (34)

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

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/27955, first published .
Automatic Extraction of Lung Cancer Staging Information From Computed Tomography Reports: Deep Learning Approach

Automatic Extraction of Lung Cancer Staging Information From Computed Tomography Reports: Deep Learning Approach

Automatic Extraction of Lung Cancer Staging Information From Computed Tomography Reports: Deep Learning Approach

Authors of this article:

Danqing Hu1, 2 Author Orcid Image ;   Huanyao Zhang1, 2 Author Orcid Image ;   Shaolei Li3 Author Orcid Image ;   Yuhong Wang1, 2 Author Orcid Image ;   Nan Wu3 Author Orcid Image ;   Xudong Lu1, 2 Author Orcid Image
Article Authors Cited by (17) Tweetations (5) Metrics

Journals

  1. Hu D, Li S, Zhang H, Wu N, Lu X. Using Natural Language Processing and Machine Learning to Preoperatively Predict Lymph Node Metastasis for Non–Small Cell Lung Cancer With Electronic Medical Records: Development and Validation Study. JMIR Medical Informatics 2022;10(4):e35475 View
  2. Hu D, Li S, Wu N, Lu X. A Multi-Modal Heterogeneous Graph Forest to Predict Lymph Node Metastasis of Non-Small Cell Lung Cancer. IEEE Journal of Biomedical and Health Informatics 2023;27(3):1216 View
  3. Puts S, Nobel M, Zegers C, Bermejo I, Robben S, Dekker A. How Natural Language Processing Can Aid With Pulmonary Oncology Tumor Node Metastasis Staging From Free-Text Radiology Reports: Algorithm Development and Validation. JMIR Formative Research 2023;7:e38125 View
  4. Thanoon M, Zulkifley M, Mohd Zainuri M, Abdani S. A Review of Deep Learning Techniques for Lung Cancer Screening and Diagnosis Based on CT Images. Diagnostics 2023;13(16):2617 View
  5. Feng Z, Wu X, Ma J, Li M, He G, Cao D, Yang G. DKADE: a novel framework based on deep learning and knowledge graph for identifying adverse drug events and related medications. Briefings in Bioinformatics 2023;24(4) View
  6. Gendrin A, Souliotis L, Loudon-Griffiths J, Aggarwal R, Amoako D, Desouza G, Dimitrievska S, Metcalfe P, Louvet E, Sahni H. Identifying Patient Populations in Texts Describing Drug Approvals Through Deep Learning–Based Information Extraction: Development of a Natural Language Processing Algorithm. JMIR Formative Research 2023;7:e44876 View
  7. Hu D, Liu B, Zhu X, Lu X, Wu N. Zero-shot information extraction from radiological reports using ChatGPT. International Journal of Medical Informatics 2024;183:105321 View
  8. Sim J, Huang X, Horan M, Baker J, Huang I. Using natural language processing to analyze unstructured patient-reported outcomes data derived from electronic health records for cancer populations: a systematic review. Expert Review of Pharmacoeconomics & Outcomes Research 2024;24(4):467 View
  9. Xiao T, Kong S, Zhang Z, Hua D, Liu F. A review of big data technology and its application in cancer care. Computers in Biology and Medicine 2024;176:108577 View
  10. Yasaka K, Kanzawa J, Kanemaru N, Koshino S, Abe O. Fine-Tuned Large Language Model for Extracting Patients on Pretreatment for Lung Cancer from a Picture Archiving and Communication System Based on Radiological Reports. Journal of Imaging Informatics in Medicine 2024 View
  11. Madan S, Lentzen M, Brandt J, Rueckert D, Hofmann-Apitius M, Fröhlich H. Transformer models in biomedicine. BMC Medical Informatics and Decision Making 2024;24(1) View
  12. 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
  13. Reichenpfader D, Müller H, Denecke K. A scoping review of large language model based approaches for information extraction from radiology reports. npj Digital Medicine 2024;7(1) View
  14. Cho H, Yoo S, Kim B, Jang S, Sunwoo L, Kim S, Lee D, Kim S, Nam S, Chung J. Extracting lung cancer staging descriptors from pathology reports: A generative language model approach. Journal of Biomedical Informatics 2024;157:104720 View
  15. Cherukuri K, Chen H. Investigating the Applications of AI in Oncology from NIH Funded Projects: Case study of Lung Cancer and Pancreatic Cancer. Proceedings of the Association for Information Science and Technology 2024;61(1):871 View