Surgicare
Surgicare (Surgical + Care)
SurgiCare is an AI system designed to support post-surgery patient recovery. In this repository, we focus on a wound classification model trained on an open-source dataset. Our objective is to improve the accuracy of wound detection and guide patients in managing their wound recovery efficiently.
Online Demo: https://surgicare-demo.streamlit.app/
Wound dataset: https://www.kaggle.com/datasets/ibrahimfateen/wound-classification)
Github Repo: https://github.com/PogusTheWhisper/SurgiCare.git
Pretrained Models:
- Surgicare-V1-best: https://huggingface.co/PogusTheWhisper/SurgiCare/resolve/main/SurgiCare-V1-best.keras
- Surgicare-V1-fast: https://huggingface.co/PogusTheWhisper/SurgiCare/resolve/main/SurgiCare-V1-fast-best.keras
- Surgicare-V1-mini: https://huggingface.co/PogusTheWhisper/SurgiCare/resolve/main/SurgiCare-V1-mini-best-model.keras
Result of training!!
Efficientnet B3
- Accuracy: 0.9062 Approximately 11 seconds per image.
- I used EfficientNet-B3 to train for 25 epochs, monitoring the validation loss.
MobileNetV3Large
- Accuracy: 0.7969 Approximately 5 seconds per image.
- I used MobileNetV3Large to train for 50 epochs, monitoring the validation loss.
MobileNetV3Small
- Accuracy: 0.7812 Approximately 4 seconds per image.
- I used MobileNetV3Small to train for 50 epochs, monitoring the validation loss.
- Downloads last month
- 150
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social
visibility and check back later, or deploy to Inference Endpoints (dedicated)
instead.