Introduction

Nigeria bears Africa’s highest tuberculosis (TB) burden, with over 361,000 cases reported in 2023—a 26% increase from 2022. Among high-risk groups, miners face extreme vulnerability due to silica dust exposure and limited healthcare access. Traditional screening methods are often unavailable in remote regions, leading to undiagnosed cases and preventable deaths.

‍

The Challenge

In northeast Nigeria’s mining communities, many workers had never undergone medical screening, leaving TB undetected until advanced stages. Conventional radiography requires stable infrastructure, internet connectivity, and specialist interpretation—barriers in low-resource settings. Without early detection, TB becomes a death sentence.

‍

The Solution: Infervision’s AI-Driven Ultra-Portable Radiology System

Partnering with the Janna Health Foundation and Sufabel Community Development organisations, Infervision deployed two breakthrough technologies:

· InferAir Ultra-Portable X-ray System: able to set up under 5 mins, battery powered for use in settings without electricity.

· InferRead DR Chest AI Software: able to detect and analyze chest X-rays under a minute without internet connection, with over 97% accuracy rates for TB and 20+ other abnormalities.

‍

Key Outcomes

· 200+ screenings per day in remote locations.

· First-time medical access for miners who has never received an X-ray scan.

· Early TB detection, enabling life-saving treatment before severe progression.

‍

Impact on Radiology & Global Health

For radiologists and healthcare providers, this case demonstrates:

· AI as a Driving Force: InferRead DR Chest reduces reliance on scarce specialists, providing rapid, reliable interpretations.

· Portability Expands Reach: InferAir’s ultra-portable design brings radiology to the most inaccessible regions.

· Global Blueprint: Available through the Global Fund, UNDP, and GDF Catalog, offering a blueprint for other high-burden regions.

‍

Conclusion

Infervision’s technology bridges critical gaps in TB care, proving that AI-powered radiology can save lives where traditional systems fail. This underscores the transformative potential of portable, connectivity-independent diagnostic tools in global health.

How could AI-radiology solutions address diagnostic gaps in your practice?

‍

👆Click here to download the full case study！