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About

Interfaces

This algorithm implements all of the following input-output combinations:

Model Facts

Summary

Automated Gleason grading of prostate biopsies following the Gleason Grade Group system. This version of the algorithm runs without data normalization.

Contact Information¶

Questions related to this algorithm can be addressed to:

https://www.computationalpathologygroup.eu/members/wouter-bulten/

or

https://www.computationalpathologygroup.eu/members/geert-litjens/

Additional Information¶

Please take the following limitations in to account when submitting data to this algorithm: A custom normalization algorithm is trained on the input data, though this cannot overcome all stain and scanner differences. We limit the overall processing time of each job by setting an upper bound on the number of epochs the normalization algorithm is trained. Due to the limited processing time, in some cases the normalization technique can fail. All input images should contain magnification levels that correspond to a 0.5, 1.0, and 2.0μm pixel spacing (± 0.05). The algorithm will stop if any of the input images miss one or more of these levels.

Mechanism

Validation and Performance

Uses and Directions

This algorithm was developed for research purposes only.

Warnings

Common Error Messages

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