/** * SimulationBriefing Component * * "What's happening in this assessment" page * Adapted from appoint-ready's RolePlayDialogs pattern * Explains the two "agents" and what to expect */ import React from 'react'; import './SimulationBriefing.css'; const SimulationBriefing = ({ selectedPatient, selectedWound, onStart, onBack }) => { return (
Built with: MedGemma 1.5 4B
In this demo, EWAAST functions as an AI agent designed to assess wounds using equitable visual criteria. It applies the{' '} Monk Skin Tone (MST) Scale to adapt its assessment based on the patient's skin tone.
For MST {selectedPatient?.mst_value} ({selectedPatient?.mst_category} skin), EWAAST will:
Simulated by: Synthetic Clinical Vignette
EWAAST is provided the context that the patient is a{' '} {selectedPatient?.age}-year-old {selectedPatient?.gender?.toLowerCase()} with{' '} MST {selectedPatient?.mst_value} ({selectedPatient?.mst_category}) skin tone.
The simulated scenario involves a {selectedWound?.name} wound:
Medical History: {selectedPatient?.existing_condition}
As the assessment develops, EWAAST{' '} generates a real-time clinical report {' '} using MST-adaptive visual criteria. For MST {selectedPatient?.mst_value}, this means:
Following the assessment, a{' '} self-evaluation highlighting equity considerations {' '} will be available to demonstrate how EWAAST ensures fair treatment across all skin tones.