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

Natural Language Processing (692) Clinical Information and Decision Making (1407) Electronic Health Records (1053) Machine Learning (1465) Secondary Use of Clinical Data for Research and Surveillance (366)

Published on in Vol 10, No 4 (2022): April

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/35475, first published .
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

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

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

Authors of this article:

Danqing Hu1 Author Orcid Image ;   Shaolei Li2 Author Orcid Image ;   Huanyao Zhang1 Author Orcid Image ;   Nan Wu2 Author Orcid Image ;   Xudong Lu1 Author Orcid Image
Article Authors Cited by (9) Tweetations (14) Metrics

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  6. 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
  7. Kenney R, Chen X, Shintani K, Gagnon C, Liu J, DaCosta Byfield S, Ochs L, Currie A. Validation of Non–Small Cell Lung Cancer Clinical Insights Using a Generalized Oncology Natural Language Processing Model. JCO Clinical Cancer Informatics 2024;(8) View
  8. Aleem M, Khan J, Younes A, Sabbah B, Saleh W, Migliore M. Enhancing Thoracic Surgery with AI: A Review of Current Practices and Emerging Trends. Current Oncology 2024;31(10):6232 View