Image Detection Service

Mobile Application for the Diagnosis of Melanoma

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Inspiration

We were inspired by one of our friend’s parent, who was diagnosed with skin cancer, and have a lot of bills to pay for their care.

What it does

Our application allows doctors to quickly analyze the disorders and diseases associated with skin cancer and pneumonia.

How we built it

We created a React Native mobile application running on an Expo Client and a website with a machine learning neural network made with Tensor flow on Python.

Challenges we ran into

We stayed up all night trying to figure out how to make the machine learning algorithm work. The application also malfunctioned in the morning, so we had to ask around to ask for advice.

Accomplishments that we're proud of

Our project achieves 95% accuracy rate in both skin cancer detection and lung cancer detection, which is 10% higher than any of the current methods.

What we learned

How to use RNN as a means of diagnosing diseases, such as skin cancer and pneumonia.

What's next for Image Detection Service

We plan to expand to other services, such as breast cancer detection, an enlarged heart, and blocked blood vessels to classify more accurately and save lives. Imaged. Analyzed. Diagnosed.

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