This is the original notebook of the existing model, found on “HAM10000: Skin disease classification” in Kaggle.
Original Source Link: K Scott Mader (Username). (2018). Skin Cancer MNIST: HAM10000 [Dataset]. Kaggle. https://www.kaggle.com/datasets/kmader/skin-cancer-mnist-ham10000?select=HAM10000_images_part_1 (CC BY-NC-SA 4.0)
Because the original dataset the model trained on is too big to include here, the original dataset is from “Skin Cancer MNIST: HAM10000” in Kaggle.
Original Source Link: K Scott Mader (Username). (2018). Skin Cancer MNIST: HAM10000 [Dataset]. Kaggle. https://www.kaggle.com/datasets/kmader/skin-cancer-mnist-ham10000?select=HAM10000_images_part_1 (CC BY-NC-SA 4.0)
For testing our web application, we extracted 70 random images from “Multiple Skin Disease Detection and Classification” in Kaggle for each class so that there are 10 images in each classes. This is stored in the folder “Testing_Images”.
Original Source Link: Pritpal Singh (Username). (2024). Multiple Skin Disease Detection and Classification [Notebook]. Kaggle. https://www.kaggle.com/datasets/pritpal2873/multiple-skin-disease-detection-and-classification (Apache License 2.0)
And finally, we deploy our web application on Streamlit Cloud. Link: https://iat360finalproject-ijmqhtij9x8slqt2paxxkn.streamlit.app/