Example algorithm Group 8
About
Creators:
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Image Version:
ea0b2501-c08d-4b54-905e-e07635a21dfd
Last updated:
May 17, 2024, 10:48 a.m.
Inputs:
- Generic Medical Image
- Generic Overlay (An overlay of unknown type. Legacy, please use alternative interfaces.)
Outputs:
- TIL Score (Percentage of stromal area covered by tumour infiltrating lymphocytes. Values between 0 (percent) to 100 (percent).)
- Detected Lymphocytes (Lymphocytes in stromal regions)
- Breast Cancer Segmentation for TILs (Class map with levels 1: invasive tumor, 2: tumor-associated stroma, 3: in-situ tumor, 4: healthy glands, 5: necrosis not in-situ, 6: inflamed stroma, 7: rest)
Model Facts
Summary
Unet algorithm running in png images of breast cancer tissue
Mechanism
This the unet algorithm
Validation and Performance
accuracy : 83% F1-score: 0.22 Precision: 0.13 Recall: 0.80
Uses and Directions
This algorithm was developed for research purposes only.
Warnings
No current warnings
Common Error Messages
No specific error messages except for missing data errors. In case of missing data add tissue cells
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