Project Info
This project did not submit a demo video on Devpost.
Inspiration
As immigrant children, we're aware of the difficulties our parents faced when communicating in English. This is especially apparent when talking about more complicated information, like their health. According to National Polling results, there are over 26 million people who have limited English proficiency. Additionally, about a third of adults with limited English proficiency say that they have faced language barriers when seeking healthcare. And during doctor's appointments, some of these non-English speaking patients are stuck with either inadequate understandings of translations or even no translations. They would have a hard time grasping words or phrases that are too technical for them to understand. Thus, this inspired us to create something that can bridge that communication gap and allow doctors and patients to understand each other easily.
What it does
Voice-to-Text Transcriptions: Doctors can report on the patient's situation by speaking to them in English. This report will be saved in the patient's appointment tab, which is translated to their native language. This report will be saved in the patient's appointment tab, which is translated to their native language. Voice-to-Voice Transcriptions: As the doctor finishes their sentences, their voice is immediately translated to the patient's native language. 3D Anatomy Visualizations: Allows the patient to actively see what part of the body that doctor is talking about, as the 3D model dynamically changes through the doctor's responses.
How we built it
The project is primarily rooted within the React.js framework in the frontend, and Python in the backend. We used Vapi's API in combination with OpenAI's models to enable both voice-to-voice interactions and voice-to-text transcription. We used Gemini API to simplify and produce text-to-text translations. Also, we referred to BioDigital to procure and implement a 3D human anatomy model.
Challenges we ran into
Correctly implementing APIs and understanding their respective documentations Integrating the frontend and the backend to work flawlessly Keeping the UI/UX intuitive for both medical professionals and patients, as well as making it highly accessible for those who are less tech-savvy
Accomplishments we're proud of
We successfully created a working prototype that can handle voice input, translate it in real-time, and present it both as text and voice in another language Implementing a dynamic, real-time anatomy visualization based on real-time medical discussions
What we learned
Implementing smooth and accurate voice interactions Balancing features we wanted to add and what was more practical for our users
What's next
Expanding our translation features to support more dialects, particularly underrepresented ones, will help reach more communities. Encourage more open and personal communication between patients and their doctor.
Getting Started with Create React App
This project was bootstrapped with Create React App.
Available Scripts
In the project directory, you can run:
npm start
Runs the app in the development mode.
Open http://localhost:3000 to view it in your browser.
The page will reload when you make changes.
You may also see any lint errors in the console.
npm test
Launches the test runner in the interactive watch mode.
See the section about running tests for more information.
npm run build
Builds the app for production to the build folder.
It correctly bundles React in production mode and optimizes the build for the best performance.
The build is minified and the filenames include the hashes.
Your app is ready to be deployed!
See the section about deployment for more information.
npm run eject
Note: this is a one-way operation. Once you eject, you can't go back!
If you aren't satisfied with the build tool and configuration choices, you can eject at any time. This command will remove the single build dependency from your project.
Instead, it will copy all the configuration files and the transitive dependencies (webpack, Babel, ESLint, etc) right into your project so you have full control over them. All of the commands except eject will still work, but they will point to the copied scripts so you can tweak them. At this point you're on your own.
You don't have to ever use eject. The curated feature set is suitable for small and middle deployments, and you shouldn't feel obligated to use this feature. However we understand that this tool wouldn't be useful if you couldn't customize it when you are ready for it.
Learn More
You can learn more in the Create React App documentation.
To learn React, check out the React documentation.
Code Splitting
This section has moved here: https://facebook.github.io/create-react-app/docs/code-splitting
Analyzing the Bundle Size
This section has moved here: https://facebook.github.io/create-react-app/docs/analyzing-the-bundle-size
Making a Progressive Web App
This section has moved here: https://facebook.github.io/create-react-app/docs/making-a-progressive-web-app
Advanced Configuration
This section has moved here: https://facebook.github.io/create-react-app/docs/advanced-configuration
Deployment
This section has moved here: https://facebook.github.io/create-react-app/docs/deployment
npm run build fails to minify
This section has moved here: https://facebook.github.io/create-react-app/docs/troubleshooting#npm-run-build-fails-to-minify
Analysis
View
Metric
- 4
- 1
Figures cover GitHub contributors during the hackathon window. A co-authored commit counts in full for each author, so per-member totals add up to more than the whole-team figures.
Technology
- CSSIn code
- HTMLIn code
- JavaScriptIn code
- PythonIn code
- ReactIn code
- SupabaseIn code
- Google GeminiClaimed
- OpenAIClaimed
6 of 8 appear in the indexed code. 2 claimed on Devpost could not be matched to code, which may simply mean the tool leaves no trace in the repository.
AI coding agents
No AI coding agent signals were found in this repository.
Detected from committed agent config files and commit authorship. Absence of a signal is not proof an agent was unused.
Codebase size
Source size
69 KB
Source files
24
Counts recognized source files only; vendored directories, binaries and lockfiles are excluded, so this is smaller than the repository on disk.
Repository
Htetty/BridgeMed-AI
37 files · 3.6 MB · @ 001f9bc
Structure
Interface
14 files · 38%Screens, components and styles rendered to the user.
Application logic
8 files · 22%Domain rules, services and shared utilities.
Supporting
Layers are inferred from where files sit in the tree, not from reading the code. A project that names its directories unconventionally will read oddly here — open the file browser to check anything the diagram implies.
Languages
- JavaScript57%
- CSS27%
- Python10%
- Markdown5%
- HTML1%
Share of indexed source by file size. Binary and vendored files are excluded.
Dependencies
package.json
npm · 8- @supabase/supabase-js
- @vapi-ai/web
- lucide-react
- react
- react-audio-visualize
- react-dom
- react-router-dom
- react-scripts
Declared in the repository’s manifests at the indexed commit. A declared package is not proof it is used, and runtime dependencies are listed first.
This project’s features have not been analysed yet.
Export this project's context (description, README, evidence, key source files) to chat with an AI agent elsewhere.