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Ekyaalo Diagnostics: Enabling Digital Pathology to Democratize Breast Cancer Diagnostics in East Africa
- Program: Biomedical Engineering
- Course: EN.580.619/620 Principles and Practice of Global Health Innovation and Design
- Year: 2026
Project Description:
Breast cancer is the leading cause of cancer death in women worldwide. In East Africa, diagnostic delays average 6–11 months — far exceeding WHO’s 60-day benchmark — driven by a critical shortage of pathologists (20 for 50M+ Ugandans), centralized infrastructure, reagent stockouts, power instability, and cultural barriers. Whole-slide scanning exists only at national centers; regional facilities must physically ship samples, adding weeks of delay.
Ekyaalo Diagnostics is developing a low-cost whole-slide scanner paired with an AI-powered region-of-interest detection algorithm, enabling telepathology where commercial scanners are unaffordable and unsuitable. Following 100+ hours of field research across Uganda and Kenya, the team has developed an AI model trained on an annotated Ugandan FNAC dataset, developed alongside pathologists at Johns Hopkins, Mbarara Regional Referral Hospital, and Mulago National Referral Hospital. The system performs real-time slide adequacy checking and ROI prioritization for remote review, operating internet-agnostically and securely without capital-intensive infrastructure.
Project Photo:
The Ekyaalo Diagnostics team speaks to Makerere University BME students in Uganda while conducting field research.