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Liver Fibrosis Early Detection Using Ultrasound Images

Mamadou Bousso of Iba Der Thiam University in Senegal will develop methods for AI-based analysis of ultrasound images for cost-effective early detection of liver fibrosis caused by hepatitis B viral infection. They will improve the performance of an existing method by acquiring ultrasound data that more comprehensively encompasses the clinically-recognized stages of liver fibrosis. The expanded dataset will be used to train an AI model well-suited to capture complex patterns in imaging data. They will also establish support for healthcare professionals that facilitates the adoption and effective use of the application, including training courses, web-based and mobile phone-based tools with user-friendly interfaces, and ongoing technical support. The application would enable more screening in underserved areas, with increased early detection and awareness of liver fibrosis decreasing mortality from the disease as well as healthcare costs.

More information about Grand Challenges Senegal: Catalyzing Equitable Artificial Intelligence (AI) Use to Improve Global Health