Company or Institution
Sustainable Development Goals (SDGs)
SDG 3: Good Health and Well-being
SDG 8: Decent Work and Economic Growth
SDG 9: Industry, Innovation and Infrastructure
General description of the AI solution
Typhoid fever is one of the infectious human diseases in Africa. Out of an estimated 11–21 million cases of typhoid fever and 200,000 deaths occur worldwide each year. Other elements contribute to this situation and particularly in rural areas where patients to doctors ratio is very low, lack of medical facilities and costly tests. There are a number of tests available presently, from molecular to immunological and biochemical to microbiological. However, Users are unsatisfied due to delays in getting test results and Imprecise diagnosis. Misdiagnosis is also usually experienced. In addition, the diagnosis of Typhoid involves several levels of uncertainties. The absence of a reliable diagnosis pushes rural populations towards self-medication with all the consequences that this entails, in particular drug poisoning which can lead to death. As such, we want to develop a new method to diagnose Typhoid early, quickly, and with accurate results at a low cost.
MBOALAB is at the forefront of a movement that will impact the greater good of the healthcare system with the main goal to unlock true value from data in order to optimize patient care, accelerate research in disease prevention and treatment, saving lives and improving the quality of care for all patients, regardless of socioeconomic status. We propose an augmented AI system with two algorithms applied with the first applied on structured data, in particular symptoms and the second applied on the blood serum in order to improve the accuracy of the diagnostics.
Github, open data repository, prototype or working demo
HPC resources and/or Cloud Computing Services