Inspiration
.MedExplain One-line pitch
AI that translates complex medical reports into plain, understandable language.
Inspiration
Patients often feel lost reading medical terms in their reports. We wanted to make healthcare data more transparent.
What it does
Users upload lab reports or prescriptions. Gemini interprets the data, explains terms like “bilirubin” or “LDL,” and gives a summary of the overall condition in simple English.
How we built it
Used Gemini API for natural language simplification. OCR extracts text from uploaded images or PDFs. Flask backend serves a React UI.
Challenges we ran into
Handling medical abbreviations with multiple meanings.
Ensuring information accuracy and tone sensitivity.
Accomplishments that we're proud of
Our model achieved over 92% accuracy in explaining standard lab reports clearly.
What we learned
The power of multimodal AI in bridging medical literacy gaps.
What's next
Adding multilingual support and voice explanations for accessibility.
What it does
How I built it
Challenges I ran into
Accomplishments that I'm proud of
What I learned
What's next for Med Explain
Built With
- actions
- ai
- alt)
- api
- api)
- atlas
- auth
- auth)
- automation)
- backend
- chroma
- ci/cd
- cloud
- communication)
- compute)
- containerization)
- css
- data
- database
- database)
- deployment)
- docker
- embeddings
- engine
- extraction)
- face
- fastapi
- firebase
- flask
- for
- frontend
- functions
- gemini
- github
- html
- hugging
- integration)
- javascript
- jwt
- langchain
- llm
- login)
- model
- model)
- modern
- mongodb
- next.js
- ocr
- optional
- orchestration)
- pinecone
- react
- real-time
- run
- secure
- serverless
- styling)
- tailwind
- text
- transformers
- trending
- trpc
- type-safe
- ui
- ui)
- updates)
- user
- vector
- vercel
- websockets