WellSkin

Empowering you to maintain your skin health. An approach to detecting Skin cancer - melanoma and allergies with TensorFlow model integrated into a website and an app along with exciting features.

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Inspiration

The best protection is early detection. We aim to focus on providing care to potential patients and enhancing the general welfare of millions of people around the world.

What it does

1) The first section is self-examination, this redirects you to a youtube video that helps the user self diagnose.

2) The next is to check your risk level, many people tend to do the doctor even for a small rash, which increases the workload of a doctor. This section provides the user with a questionnaire to determine if they really need to see a dermatologist.

3) Next is Reminder alerts. This section stores all of the user's appointments and medical check-up dates.

4) A nearby dermatologist redirects you to a page for dermatologists near you. We are working on doing that in the app itself.

5) The self-help section helps the cancer patient emotionally. People are traumatized when they get to know they are diagnosed, this section points to all the therapists and counselors near the user.

6) What next is a section telling the user the journey of a cancer patient from day 1.

7) Blogs provide additional and much-required information for cancer patients

How we built it

We built the app using Flutter and Android Studio and the website using languages like html5 and CSS3. For the AI model, we used Collected data from Kaggle, Google collab, python, and TensorFlow.

Challenges We ran into

We came across a lot of new things. Apart from teamwork, we learned how an app and a website for our case come together. There were many changes we needed to make before all of us were completely satisfied. We had computational issues.

What's next for WellSkin

With better datasets, questionnaires with better medical details, and tie-ups with hospitals, we look forward to having an even more reliable app.

Built with

adobe
html5
CSS3
dart
flutter
jupyter
python
android-studio
tensorflow
keras
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