Lung cancer risk estimation on thorax CT scans - DSB2017 grt123
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ffdd0ac4-315e-4879-84ce-8cda68e03989 — April 13, 2021
Associated publications:
Jacobs C, Setio AAA, Scholten ET, et al.. Deep Learning for Lung Cancer Detection on Screening CT Scans: Results of a Large-Scale Public Competition and an Observer Study with 11 Radiologists. Radiology: Artificial Intelligence. 2021;3(6).
Summary
This algorithm analyzes non-contrast CT scans of the thorax and predicts the lung cancer risk. The algorithm is described in this publication by Fangzhou Liao, Ming Liang, Zhe Li, and Xiaolin Hu and the code is publicly available on Github.
This algorithm was developed as part of the Kaggle Data Science Bowl in 2017 and won the first place in this challenge.
Image courtesy of Fangzhou Liao et al. in the previously mentioned paper.
Mechanism
The algorithm is described in this publication by Fangzhou Liao, Ming Liang, Zhe Li, and Xiaolin Hu.
Interfaces
This algorithm implements all of the following input-output combinations:
Validation and Performance
Left empty by the Algorithm Editors
Uses and Directions
This algorithm was developed for research purposes only.
Warnings
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Common Error Messages
Left empty by the Algorithm Editors
Information on this algorithm has been provided by the Algorithm Editors,
following the Model Facts labels guidelines from
Sendak, M.P., Gao, M., Brajer, N. et al.
Presenting machine learning model information to clinical end users with model facts labels.
npj Digit. Med. 3, 41 (2020). 10.1038/s41746-020-0253-3