EpiCast
Multi-modal AI epidemiological surveillance system for West Africa
View on GitHubFirst Place, Google Health AI MedGemma Impact Challenge, 2026. USD 30,000 grand prize, selected first from over 850 teams and 6,500 entrants worldwide.
Multi-Modal AI Epidemiological Surveillance System
Built a mobile-first disease surveillance platform for West Africa (ECOWAS) combining fine-tuned medical LLMs with audio AI for syndromic monitoring and cough-based respiratory illness detection.
Fine-tuned and quantized MedGemma 4B to GGUF format for on-device inference, enabling a complete offline AI stack on mobile devices with sub-second response times and zero cloud dependency.
Integrated MedSigLIP for clinical image triage, HeAR audio models for cough classification, and a multilingual NLP pipeline trained on 9,700+ corpus-grounded examples across French, Hausa, and Yoruba.
Designed a 4-tab mobile interface (Dashboard, Intake, Alerts, Reports) with real-time syndromic heatmaps and structured WHO IDSR situation reports generated by MedGemma 27B.
Tech Stack: MedGemma 4B/27B, MedSigLIP, Google HeAR, FastAPI, RunPod Serverless, Python