Published on in Vol 23, No 8 (2021): August

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/26256, first published .
Artificial Intelligence–Based Prediction of Lung Cancer Risk Using Nonimaging Electronic Medical Records: Deep Learning Approach

Artificial Intelligence–Based Prediction of Lung Cancer Risk Using Nonimaging Electronic Medical Records: Deep Learning Approach

Artificial Intelligence–Based Prediction of Lung Cancer Risk Using Nonimaging Electronic Medical Records: Deep Learning Approach

Journals

  1. Ahmed F, Khan A, Ansari H, Haque A. A Systems Biology and LASSO-Based Approach to Decipher the Transcriptome–Interactome Signature for Predicting Non-Small Cell Lung Cancer. Biology 2022;11(12):1752 View
  2. Koshechkin K. Regulation of artificial intelligence in medicine. Patient-Oriented Medicine and Pharmacy 2023;1(1):32 View
  3. Li S, Deng L, Zhang X, Chen L, Yang T, Qi Y, Jiang T. Deep Phenotyping of Chinese Electronic Health Records by Recognizing Linguistic Patterns of Phenotypic Narratives With a Sequence Motif Discovery Tool: Algorithm Development and Validation. Journal of Medical Internet Research 2022;24(6):e37213 View
  4. Yu X, Zhou S, Zou H, Wang Q, Liu C, Zang M, Liu T. Survey of deep learning techniques for disease prediction based on omics data. Human Gene 2023;35:201140 View
  5. Raghu V, Walia A, Zinzuwadia A, Goiffon R, Shepard J, Aerts H, Lennes I, Lu M. Validation of a Deep Learning–Based Model to Predict Lung Cancer Risk Using Chest Radiographs and Electronic Medical Record Data. JAMA Network Open 2022;5(12):e2248793 View
  6. Chen A, Chen D. Simulation of a machine learning enabled learning health system for risk prediction using synthetic patient data. Scientific Reports 2022;12(1) View
  7. Nguyen P, Rathod A, Chapman D, Prathapan S, Menon S, Morris M, Yesha Y. Active Semi-Supervised Learning via Bayesian Experimental Design for Lung Cancer Classification Using Low Dose Computed Tomography Scans. Applied Sciences 2023;13(6):3752 View
  8. Adams S, Mikhael P, Wohlwend J, Barzilay R, Sequist L, Fintelmann F. Artificial Intelligence and Machine Learning in Lung Cancer Screening. Thoracic Surgery Clinics 2023;33(4):401 View
  9. El-Sherbini A, Hassan Virk H, Wang Z, Glicksberg B, Krittanawong C. Machine-Learning-Based Prediction Modelling in Primary Care: State-of-the-Art Review. AI 2023;4(2):437 View
  10. Pungitore S, Subbian V. Assessment of Prediction Tasks and Time Window Selection in Temporal Modeling of Electronic Health Record Data: a Systematic Review. Journal of Healthcare Informatics Research 2023;7(3):313 View
  11. Khodadadi A, Ghanbari Bousejin N, Molaei S, Kumar Chauhan V, Zhu T, Clifton D. Improving Diagnostics with Deep Forest Applied to Electronic Health Records. Sensors 2023;23(14):6571 View
  12. Gandhi Z, Gurram P, Amgai B, Lekkala S, Lokhandwala A, Manne S, Mohammed A, Koshiya H, Dewaswala N, Desai R, Bhopalwala H, Ganti S, Surani S. Artificial Intelligence and Lung Cancer: Impact on Improving Patient Outcomes. Cancers 2023;15(21):5236 View
  13. Ma Z, Lv J, Zhu M, Yu C, Ma H, Jin G, Guo Y, Bian Z, Yang L, Chen Y, Chen Z, Hu Z, Li L, Shen H. Lung cancer risk score for ever and never smokers in China. Cancer Communications 2023;43(8):877 View
  14. Chen H, Wang H, Lin C, Yang R, Lee C. Lung Cancer Prediction Using Electronic Claims Records: A Transformer-Based Approach. IEEE Journal of Biomedical and Health Informatics 2023;27(12):6062 View
  15. Grandal N, Muzumdar S, Khan N, Ahmed N. Artificial intelligence will transform healthcare: considerations for adoption and scale. British Journal of Healthcare Management 2024;30(1):8 View
  16. Panda S, Naga Ramesh J, Ghosh H, Rahat I, Sobur A, Bijoy M, Yesubabu M. Deep Learning in Medical Imaging: A Case Study on Lung Tissue Classification. EAI Endorsed Transactions on Pervasive Health and Technology 2024;10 View
  17. Uppal S, Kumar Shrivastava P, Khan A, Sharma A, Kumar Shrivastav A. Machine learning methods in predicting the risk of malignant transformation of oral potentially malignant disorders: A systematic review. International Journal of Medical Informatics 2024;186:105421 View
  18. Ghosh H, Rahat I, Ravindra J, J B, Ullah Khan M, Somasekar J. Convolutional Neural Networks in Malaria Diagnosis: A Study on Cell Image Classification. EAI Endorsed Transactions on Pervasive Health and Technology 2024;10 View
  19. Chen A, Wu E, Huang R, Shen B, Han R, Wen J, Zhang Z, Li Q. Development of Lung Cancer Risk Prediction Machine Learning Models for Equitable Learning Health System: Retrospective Study. JMIR AI 2024;3:e56590 View
  20. Lee W, Yoo K, Noh J, Lee M. Health expenditure trajectory and gastric cancer incidence in the National Health Insurance Senior Cohort: a nested case-control study. BMC Health Services Research 2024;24(1) View
  21. Zhou T, Zhu P, Xia K, Zhao B. A Predictive Model Integrating AI Recognition Technology and Biomarkers for Lung Nodule Assessment. The Thoracic and Cardiovascular Surgeon 2024 View

Books/Policy Documents

  1. Zareian F, Rezaei N. Lung Cancer Diagnosis and Treatment: An Interdisciplinary Approach. View
  2. Baptiste J, Barta J, Patel S, Thomson C, Tukey M, Michaud G. Lung Cancer Screening. View
  3. Yadav S, Hasija Y. Computational Intelligence in Oncology. View
  4. Yang H, Li Y. Artificial Intelligence, Machine Learning, and Deep Learning in Precision Medicine in Liver Diseases. View
  5. Devkar A, Kanade A. AI Technologies for Information Systems and Management Science. View