Baseline algorithm
About
Creator:
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Version:
4186b9b5-de89-40cb-af46-00e1289450c9
Last updated:
June 18, 2022, 9:38 p.m.
Inputs:
- CT Image (Any CT image)
Outputs:
- Lung nodule malignancy risk (Malignancy risk of lung nodule detected in a chest CT ranging between 0 to 1 with 0 being the lowest malignancy risk and 1 being the highest malignancy risk)
- Lung nodule type (The sub-type / texture of a lung nodule detected in a chest CT. Labels follow this mapping: 0: "non-solid", 1: "part-solid", 2: "solid".)
Model Facts
Summary
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Mechanism
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Validation and Performance
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Uses and Directions
This algorithm was developed for research purposes only.
Warnings
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Common Error Messages
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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