Clinical AI Assistant
Lets a nurse chart by talking instead of typing. Runs on the hospital’s own hardware, so patient data never leaves the building.
- Software Engineer, AI Research
- Purdue University
- 2024 to 2025
- Research
- ~40%less documentation overhead for nurses
Problem
Clinical AI has to be useful without being careless.
Privacy, latency, and interpretability matter as much as the model does, and a nurse mid-shift will not wait on a round trip to someone else’s API.
Approach
I built a clinical assistant with hard privacy constraints: nothing leaves the device that doesn’t have to.
Local speech-to-text, self-hosted models, and an interface a nurse could use one-handed while doing something else.
How it works
A voice-first clinical assistant a nurse can use one-handed, mid-shift.
Flutter and TypeScript application layer built around voice-first clinical workflows: tasks, reminders, and patient vitals.
Self-hosted LLaMA 3.2 with a zero-API, on-device speech pipeline, so protected health information never leaves the device.
Deployed and tested across Indiana hospitals.
Screens

Voice-first home screen. The microphone is the primary control.

Tasks and reminders, dictated hands-free during a shift.

Patient vitals, captured without touching a keyboard.
Impact
Time nurses got back at the bedside instead of at a keyboard.
Presented at the Purdue Spring Research Conference.