nishnarudkar/NeuroLynk-AI
An interoperable healthcare AI agent that screens for Parkinson's disease from speech biomarkers — producing explainable predictions, LLM-generated clinical summaries, and FHIR R4 DiagnosticReports in a single API call.
SUMMARY AI summary by gpt-5-mini
NeuroLynk AI is an interoperable, multi-agent healthcare AI for screening Parkinson’s disease from speech biomarkers. It’s intended for clinicians, healthcare platforms, and developers who need automated, explainable screening and FHIR-native outputs integrated into workflows. Key features: - Single POST /agent/screen call orchestrates three agents: speech screening (XGBoost on 753 vocal features), clinical summary (LLM-generated narrative), and FHIR Report (HL7 FHIR R4 DiagnosticReport with SNOMED CT mapping). - Explainability via SHAP TreeExplainer providing top feature attributions. - A2A protocol and SHARP extension support for patient/encounter propagation. - API endpoints for reporting, health checks, agent schema, and JSON-RPC integration. - MLOps: MLflow, DVC, Evidently; serverless deployment (Google Cloud Run); local FastAPI/Uvicorn setup.
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Owner
I am an undergraduate student in AIML currently in my 3rd year in Ramrao Adik Institute of Technology, D.Y.Patil University.
Dates
| Created on GitHub | 2026-05-08 |
| Last push | 2026-05-09 |
| First seen here | 2026-05-09 |
| Last fetched | 2026-05-09 14:19 |
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