Inspiration
We wanted to make sure proper guidance to recovery is accessible to every individual regardless of theri stay in the hospital.
What it does
It helps the patient to recover after their operation, by monitoring, giving dietary restrictions, guidance on a weekly basis.
How we built it
We utilized the repositories provided, created how own customized MCPs, connected it to the agent and let it understand our synthesized FHIR patient data to provide reasonable outputs.
Challenges we ran into
The greatest challenge was to fine tune the model to understand the data correctly and provide appropriate output.
Accomplishments that we're proud of
The quality of data, the correlation between the agent and the MCP.
What we learned
To create ETL pipelines, create customized MCP.
What's next for PalliSync
Accessible via mobile applications for maximum convenience.
Built With
- gcp
- python
Log in or sign up for Devpost to join the conversation.