oncoIQ

Inspiration

After learning more about the role pathologists play in diagnosing cancer from Joe's mom, we were inspired to create an app that assists physicians using machine learning technology.

What it does

• Analyze histopathological images to highlight high-risk tissues
• Assists pathologists in making diagnostics and allows them to easily categorize samples
• Allows for rapid turn around time for intraoperative consolation and remote pathology

How we built it

• ReactJS frontend, Bootstrap for CSS, Flask backend, and SQLite for database
• A custom trained machine learning model deployed in the cloud
• The model is trained with datasets from Case Western Reserve University

Challenges we ran into

• Working with 2 different languages (Python, and JavaScript)
• Not a lot of prior experience with frontend dev
• User authentication
• time crunch
• Sleep

Accomplishments that we're proud of

• A fully functional full-stack app in 24 hours!
• Accurate machine learning model

Built With

• clarifai
• flask
• machine-learning
• react