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README.md

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-license: apache-2.0
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+---
+license: apache-2.0
+tags:
+- vision
+- image-classification
+---
+
+### (GI) Gastrointestinal Adenocarcinoma
+
+This model can additionally be run on our [pathology reports platform](https://www.pathologyreports.ai/marketplace/browse/a7d3b949-d1dd-4a5c-bfa7-a9fe3cb8d79a)
+
+Credits: Dr. Mohamed Al-Yousef (King Fahd Hospital of the University, Saudi Arabia)
+
+### Introduction
+
+This H&E colorectal carcinoma tissue classifier was developed using transfer learning on a histology optimized version of the VGG19 CNN [(DOI: 10.1038/s42256-019-0068-6)](https://doi.org/10.1038/s42256-019-0068-6) and trained to recognize colorectal adenocarcinoma and other surrounding tissue elements.
+
+Annotations were carried out on batches of image tiles (dimensions: 512 x 512 px) grouped using image-based clustering [(HAVOC, DOI: 10.1126/sciadv.adg1894)](https://doi.org/10.1126/sciadv.adg1894) from 8 publicly available TCGA-COAD H&E-stained whole slide images. Validation testing was carried out on non-overlapping image tiles from the same cases.
+
+
+### Classes
+
+1. Connective tissue
+2. Edge of Tumor
+3. Edge Of Tumor And Inflammtory Cells
+4. Epithelial Pattern
+5. Neoplastic epithelial pattern
+6. Inflammatory Cells
+7. Mucin
+8. Smooth muscle
+9. Acute hemorrhage
+10. Blank space
+11. Necrosis
+12. Neoplastic Epithelial Pattern - Signet Ring
+14. Non-neoplastic epithelial pattern
+
+This information can be found in the inference.json file
+
+### Evaluation Metrics
+
+Classifier validation can be found on the [pathology reports platform](https://www.pathologyreports.ai/marketplace/browse/a7d3b949-d1dd-4a5c-bfa7-a9fe3cb8d79a)