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AI-Powered Healthcare for All
Developing AI-powered diagnostic tools, telemedicine platforms, and health information systems that bridge the gap between urban medical centers and rural communities across Africa.
3M+
Patients Screened
85%
Diagnostic Accuracy
75%
Faster Triage
500+
Health Facilities
Healthcare in Africa faces unique challenges: a shortage of medical specialists, limited diagnostic equipment in rural areas, and fragmented health information systems. AI has the potential to address these challenges at scale.
Our Healthcare AI research focuses on three key areas: AI-assisted diagnostics that help clinicians detect conditions earlier, telemedicine solutions that connect patients with specialists, and health data systems that enable better population health management.
All our healthcare AI work is grounded in responsible AI principles, ensuring that models are fair, transparent, and clinically validated before deployment.
Understanding the unique obstacles we're working to overcome.
Many African countries have fewer than 1 specialist per 100,000 people, compared to 100+ in developed nations.
Late diagnosis of conditions like tuberculosis, malaria, and cancer leads to preventable deaths and higher treatment costs.
Rural clinics often lack reliable electricity, internet, and diagnostic equipment needed for modern healthcare.
Patient records are scattered across facilities, making it difficult to track health outcomes and manage chronic conditions.
The methods and techniques we've developed to address these challenges.
Deep learning models that analyze medical images, X-rays, and microscopy slides to assist with diagnosis.
AI systems that help clinicians with differential diagnosis, treatment recommendations, and risk assessment.
All our healthcare AI tools work without internet connectivity, essential for rural deployment.
Rigorous testing with local clinicians and patient populations before any deployment.
Measurable outcomes from our research and deployments.
3M+
Patients Screened
Our diagnostic tools have been used to screen over 3 million patients across East Africa.
85%
Diagnostic Accuracy
Our TB screening model achieves 85% sensitivity, comparable to expert radiologists.
75%
Faster Triage
AI-assisted triage reduces time-to-treatment by 75% in partner clinics.
500+
Health Facilities
Our solutions are deployed in over 500 health facilities across 4 countries.
Hassan, F., Okonkwo, A., et al.
Adeyemi, G., Hassan, F., et al.
Computer vision tool for detecting TB, pneumonia, and other conditions from chest X-rays.
Partners:
Ministry of Health Kenya, USAID
Voice-enabled health assistant for symptom checking and health information in Swahili.
Partners:
WHO Africa, Tanzania MoH
Fatima Hassan
Research Lead
Dr. Amara Okonkwo
Clinical Advisor
We're always looking for collaborators, partners, and talented researchers to advance this work.