

Early Detection. Zero Radiation.
Introducing
Building Respiratory Evidence for AI Tools and Health Equity




















Build the world’s first open-access, geographically diverse respiratory dataset combining thoracic ultrasound (TUS), chest X-ray, CT (adults), clinical data, lab reports, and respiratory audio.
Recruit a cohort of 15,000 –18,000 participants across India, South Africa, and Nigeria, building a target subset of 3,500 confirmed adult and pediatric TB and pneumonia cases.
Develop prototype AI-enabled CAD models to test automated interpretation of POCUS-based TUS for screening and triage of TB and community-acquired pneumonia in adults and children.
A 23-month initiative, commencing October 2025
Enabling rapid, early screening and triage for TB and pneumonia in adults and children through portable, radiation-free ultrasound powered by AI, especially in low-resource and remote settings.
A high-quality, globally diverse open-access dataset combining thoracic ultrasound, chest X-ray, chest CT, clinical data, and audio signals to accelerate research and innovation in respiratory diagnostics.
Prototype AI tools that support community and primary care providers in identifying presumptive TB and pneumonia where specialist expertise and diagnostics are limited.
Solutions that are patient-centric, affordable, and scalable that bring high-quality diagnostic support closer to underserved communities and reduce preventable deaths.
Open science and evidence generation to support future research, improve clinical decision-making, and inform next-generation diagnostic tools and policies.