Abstract:
Mamadou Lamine MBOUP's (University of Thies, Expected 2022) research focuses on using ML methods over ultrasound data to perform early diagnosis and identification of liver damage within chronic liver disease patients and to classify said patients according to their severity. Especially in areas where chronic liver diseases, such as hepatitis, are prevalent, and liver cirrhosis and cancer are a significant health burden on the community, using ML methods to perform early diagnosis of these syndromes based on a low-cost modality like ultrasound would be extremely impactful. Mamdou's work investigates using supervised and unsupervised classical and deep learning methods to solve this problem, using data from a cohort of patients at the Aristide Le Dantec University Hospital Center. In past work, Mamadou has investigated algorithms for image compression, as well as investigated other health tasks in the cancer area.