Inspiration

I wanted to make an app that people around the world could use at home to check privately whether or not they were at risk of skin cancer.

What it does

It is a cross-platform mobile application, based on a web app, that allows users to take or submit a picture of a mole that they suspect is cancerous. A self-developed algorithm analyzes the image and predicts whether or not the mole is cancerous, along with a confidence level. It then allows users to track their moles over time, providing data and graphs as visual aids to help determine whether or not the moles are becoming more dangerous.

How I built it

I used Adobe’s Phonegap, which builds the Android, iOS, and Windows versions of the mobile app from the framework created in HTML/CSS/JQuery. Images are processed using a machine learning algorithm that integrates OpenCV and is trained on a public, HIPAA-compliant data set containing over a thousand images of potentially cancerous moles. This prediction may be improved by the user providing basic data that may put them at greater risk of skin cancer.

What I learned

I gained valuable technical skills technical skills, like working with databases, algorithms, and machine learning

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