Update README.md

README.md

@@ -4,6 +4,9 @@ pipeline_tag: image-classification
 tags:
 - medical
 ---
+## Model Purpose
+Classify whether there is cancer or not in CT-scan images of the lungs.
+
 ## Model Details
 
 This model is trained on 224X224 Grayscale images which were originally CT-scans
@@ -15,7 +18,7 @@ I also used this tutorial.[Swin Transformer (tiny-sized model)](https://colab.re
 
 ## Uses
 
-The model can be used to classify JPG images of CT scans into either cancer positive or
+The model can be used to classify JPG images of CT-scans into either cancer positive or
 Cancer negative groups.
 I think it would work okay for any image classification task.
 
@@ -25,6 +28,7 @@ I think it would work okay for any image classification task.
 
 The model was trained on data originally obtained from the National Cancer Institute
 Imaging Data Commons. https://portal.imaging.datacommons.cancer.gov/explore/
+Specifically data from the National Lung Screening trial.
 The data set used consisted of about 11,000 images which were transformed CT scans
 some of which contained Cancerous Nodules and some that did not.
 
@@ -32,7 +36,7 @@ some of which contained Cancerous Nodules and some that did not.
 ## How to Use
 
 Upload a grayscale JPG into the model inference section and it will cast a prediction.
-One comes included in this repo. If the image contains an X, it is a negative cancer image.
+Some are included in this repo. If the image contains an X, it is a negative cancer image.
 If an image name contains a Y it is positive.