OralCam is a mobile health system that allows users to self-examine their oral health conditions. I worked on this project during my summer research internship at UCLA HCI Lab, and I was advised by Prof. Xiang Anthony Chen.
With collaborated dentists, OralCam supports assessments of 5 common diseases. The project helps the patients in areas without abundant dental resources be aware of their oral health conditions and improve their habits with an easy-to-use web-based app.
My main contributions included:
- Literature review of relevant areas, like interactive machine learning and mobile health research.
- Designed and conducted the user study.
- Academic writing.
- Developed the full-stack application independently.
1. Front-end: Vue.js, Element-UI, TypeScript, Node.js
2. Back-end: Python, Flask, PyTorch, OpenCV
3. Continuous Integration: Docker, Jest
- Literature review of relevant areas, like interactive machine learning and mobile health research.
- Designed and conducted the user study.
- Academic writing.
- Developed the full-stack application independently.
1. Front-end: Vue.js, Element-UI, TypeScript, Node.js
2. Back-end: Python, Flask, PyTorch, OpenCV
3. Continuous Integration: Docker, Jest
The paper was accepted by SIGCHI 2020, and we received a 4.0/5.0 average score from reviewers, which was higher than 90% of submitted papers according to the official post on twitter.
It is one of the best paper honorable mentioned.
You can read the paper here.
