Pratibimb Home
About

A digital twin you can question before you advise.

Pratibimb (प्रतिबिम्ब, “reflection”) fuses a simulated health record with simulated wearable streams, keeps a physiological model in sync with them, and predicts adverse glucose events in advance. It is a proof of concept on synthetic data, not a medical device.

Clinician consoleModel cardPhoto credits
Architecture

  1. 01
    Truth simulator
    240 synthetic patients × 28 days; richer than the twin
    Synthetic data
  2. 02
    EHR + wearables
    FHIR R4 bundles; CGM, HR, HRV, steps, sleep
    Two streams
  3. 03
    Twin
    Glucose–insulin ODE + 64-member EnKF, 4-h forecasts
    Physiology
  4. 04
    Risk layer
    LightGBM on twin + CGM features, TreeSHAP drivers
    Machine learning
  5. 05
    API
    FastAPI REST + WebSocket replay; static demo export
    Python
  6. 06
    Console
    Next.js clinician console, What-If Lab
    Web

The twin never sees the simulator’s hidden labels or parameters; every metric is twin-versus-truth on held-out patients.

Team Stack Underflow

Yashvardhan Thanvi
Team lead
Birla Institute of Technology (BIT Mesra), Off Campus Jaipur
Devesh Jain
Team member
Birla Institute of Technology (BIT Mesra), Off Campus Jaipur