MEDISCAN

Inspiration

We initially thought of this idea because of the statistics for pneumonia that we noticed. It was eye-opening to see how many deaths were caused by undiagnosed pneumonia.

What it does

MediScan uses machine learning to detect pneumonia scans based on x-ray scans collected.

How we built it

We used HTML, CSS, ReactJS, TailwindCSS, Kaggle for the data, and TensorFlow and Python for the machine learning.

Challenges we ran into

We faced issues during our development process, including time restraints and a lack of experience with machine learning.

Accomplishments that we're proud of

Overall, we are very proud of the outcome as we were able to effectively create a machine learning program to do something impactful for the world.

What we learned

We learned a lot about machine learning and react during this long process.

What's next for MediScan

Next, we hope to bring expand MediScan to detect more diseases, such as other respiratory diseases and cancers.

Built With

• css
• html
• javascript
• kaggle
• opencv
• python
• react
• tensorflow