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. Development of a Semi-Automated Chart Review for Assessing the Development of Radiation Pneumonitis: using Natural Language Processing (Preprint). JMIR Medical Informatics 2021 View