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

Artificial Intelligence (1371) Lung Cancer (34) Innovations and Technology for Cancer Prevention and Screening (147)

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

Authors of this article:

Marvin Chia-Han Yeh1, 2 Author Orcid Image ;   Yu-Hsiang Wang3 Author Orcid Image ;   Hsuan-Chia Yang4, 5 Author Orcid Image ;   Kuan-Jen Bai6, 7, 8 Author Orcid Image ;   Hsiao-Han Wang1, 2, 4, 9 Author Orcid Image ;   Yu-Chuan Jack Li1, 2, 4, 5, 9 Author Orcid Image
Article Authors Cited by (28) Tweetations (32) Metrics

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  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
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  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
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