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

Clinical Information and Decision Making (1328) Imaging Informatics (187) Machine Learning (1385) Innovations in Cancer Diagnostic and Decision Support (50)

Published on in Vol 22, No 8 (2020): August

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/16709, first published .
Reproducible Machine Learning Methods for Lung Cancer Detection Using Computed Tomography Images: Algorithm Development and Validation

Reproducible Machine Learning Methods for Lung Cancer Detection Using Computed Tomography Images: Algorithm Development and Validation

Reproducible Machine Learning Methods for Lung Cancer Detection Using Computed Tomography Images: Algorithm Development and Validation

Authors of this article:

Kun-Hsing Yu1, 2, 3 Author Orcid Image ;   Tsung-Lu Michael Lee4 Author Orcid Image ;   Ming-Hsuan Yen5, 6 Author Orcid Image ;   S C Kou2 Author Orcid Image ;   Bruce Rosen7, 8 Author Orcid Image ;   Jung-Hsien Chiang6 Author Orcid Image ;   Isaac S Kohane1, 8 Author Orcid Image
Article Authors Cited by (46) Tweetations (19) Metrics

Journals

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  15. Tsai P, Lee T, Kuo K, Su F, Lee T, Marostica E, Ugai T, Zhao M, Lau M, Väyrynen J, Giannakis M, Takashima Y, Kahaki S, Wu K, Song M, Meyerhardt J, Chan A, Chiang J, Nowak J, Ogino S, Yu K. Histopathology images predict multi-omics aberrations and prognoses in colorectal cancer patients. Nature Communications 2023;14(1) View
  16. Bhavani K, Gopalakrishna M. COMPARATIVE ANALYSIS OF TRADITIONAL CLASSIFICATION AND DEEP LEARNING IN LUNG CANCER PREDICTION. Biomedical Engineering: Applications, Basis and Communications 2023;35(02) View
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  21. Reddy N, Khanaa V. Diagnosing and categorizing of pulmonary diseases using Deep learning conventional Neural network. International Journal of Experimental Research and Review 2023;31(Spl Volume):12 View
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Books/Policy Documents

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