What it does
DetAll is a group of medical tools based on the web which allow doctors to perform various types of analysis only through an image.
It consists of three main sections as of now: Eyes, COVID and Skin.
- Eyes - performs functions around the eye like cataract detection, diabetic retinopathy detection and redness levels (uveitis) detection
- COVID - analyses CT scans of lungs for detection of COVID-19
- Skin - detects malignant and benign type of skin cancer
How I built it
Trained Models on Google Teachable Machine
Then loaded that models and used streamlit to run it on localhost. (You can also run it on Colab Notebook Directly ,Link is provided below and in github)
Used Datasets from :
Eyes: https://github.com/javathunderman/retinopathy-dataset https://github.com/yiweichen04/retina_dataset
Skin: https://www.kaggle.com/fanconic/skin-cancer-malignant-vs-benign
Challenges I ran into
Training Models using Teachable Machine
Accomplishments that I'm proud of
Used Streamlit to build Frontend for first time
What I learned
Building UI using Streamlit Using multiple Machine Learning Models for single project
What's next for DetAll
- For future use-cases, direct integration with medical hardware and devices is possible which allows better quality computer vision analysis and faster results.
- Adding more features to Model like detecting type of Disease
- Creating Mobile App using Tflite (currently we have web app)
Built With
- python
- tensorflow
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