Published on in Vol 6, No 1 (2018): Jan-Mar

Automated Information Extraction on Treatment and Prognosis for Non–Small Cell Lung Cancer Radiotherapy Patients: Clinical Study

Automated Information Extraction on Treatment and Prognosis for Non–Small Cell Lung Cancer Radiotherapy Patients: Clinical Study

Automated Information Extraction on Treatment and Prognosis for Non–Small Cell Lung Cancer Radiotherapy Patients: Clinical Study

Journals

  1. Chen S, Wu S. Identifying Lung Cancer Risk Factors in the Elderly Using Deep Neural Networks: Quantitative Analysis of Web-Based Survey Data. Journal of Medical Internet Research 2020;22(3):e17695 View
  2. Wang L, Luo L, Wang Y, Wampfler J, Yang P, Liu H. Natural language processing for populating lung cancer clinical research data. BMC Medical Informatics and Decision Making 2019;19(S5) View
  3. Datta S, Bernstam E, Roberts K. A frame semantic overview of NLP-based information extraction for cancer-related EHR notes. Journal of Biomedical Informatics 2019;100:103301 View
  4. Solarte Pabón O, Torrente M, Provencio M, Rodríguez-Gonzalez A, Menasalvas E. Integrating Speculation Detection and Deep Learning to Extract Lung Cancer Diagnosis from Clinical Notes. Applied Sciences 2021;11(2):865 View
  5. McKenzie J, Rajapakshe R, Shen H, Rajapakshe S, Lin A. A Semiautomated Chart Review for Assessing the Development of Radiation Pneumonitis Using Natural Language Processing: Diagnostic Accuracy and Feasibility Study. JMIR Medical Informatics 2021;9(11):e29241 View
  6. Wendelboe A, Saber I, Dvorak J, Adamski A, Feland N, Reyes N, Abe K, Ortel T, Raskob G. Exploring the Applicability of Using Natural Language Processing to Support Nationwide Venous Thromboembolism Surveillance: Model Evaluation Study. JMIR Bioinformatics and Biotechnology 2022;3(1):e36877 View
  7. Zhou B, Yang G, Shi Z, Ma S. Natural Language Processing for Smart Healthcare. IEEE Reviews in Biomedical Engineering 2024;17:4 View