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# 2024 Virufy Diagnosis AI |
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Respiratory diseases, including COVID-19, require prompt detection and action. Traditional methods often fall short, especially in low-resource settings. This project introduces an AI-powered mobile app that analyses cough sounds recorded via smartphones to detect and predict respiratory outbreaks. Using generative AI, the app generates real-time insights and forecasts disease spread, improving early detection and enabling timely public health interventions. This approach also supports better vaccine distribution and preparation for future outbreaks, revolutionising respiratory health monitoring
Amil Khanzada is a PhD student at the University of Fukui in Japan, pursuing a research thesis in applying marketing and nudge theory to accelerate the collection of AI training data for smartphone-based tools to diagnose respiratory diseases from breathing sounds. Prior, Amil was a student at UC Berkeley and Stanford pursuing an MBA and MSCS in AI. A data guru, Amil has worked as a software developer and consultant both in the Silicon Valley and Tokyo, in the database and cybersecurity fields, prior to starting his international nonprofit AI research organization Virufy in response to the COVID-19 pandemic. more
Nanyang Technological University
Targeted antimicrobial treatment for resistant infections
Early detection and non-invasive correction of breech pregnancies
