Artificial Intelligence for screening and management of health conditions in LMICs

Programme overview:
This MRC-funded doctoral training partnership (DTP) brings together cutting-edge molecular and analytical sciences with innovative computational approaches in data analysis to enable students to address hypothesis-led biomedical research questions. This is a 4-year programme whose first year involves a series of taught modules and two laboratory-based research projects that lead to an MSc in Interdisciplinary Biomedical Research. The first two terms consist of a selection of taught modules that allow students to gain a solid grounding in multidisciplinary science. Students also attend a series of masterclasses led by academic and industry experts in areas of molecular, cellular and tissue dynamics, microbiology and infection, applied biomedical technologies and artificial intelligence and data science. During the third and summer terms students conduct two eleven-week research projects in labs of their choice.

Project overview:
During the Sixtieth World Health Assembly, the World Health Organization (WHO) recognized the importance of Medical Devices to support the quality of healthcare services in low and middle income countries (LMICs). The lack of appropriate medical devices for screening and early diagnosis was recognized as a barrier to the achievement of the UN Global Sustainable Goals (SDGs), hindering human rights.

This PhD project will investigate the extent to which Key Enabling Technologies (KETs) such as Artificial Intelligence (AI), big-data and mobile phones can be used to design appropriate medical devices to empower patients and local healthcare services in LMICs, in particular in Sub-Saharan Africa (SSA). The project will focus on two common medical conditions. Pneumonia is a leading cause of death in children and adults worldwide but particularly in LMICs. Self-assessment of symptoms and diagnostic aids in the form of Rapid Diagnostic Tests (RDTs) have been shown to improve pneumonia screening, detection and treatment. This project is designed to investigate how KETs can be used in LMICs to identify pneumonia and the origin of infection (e.g., viral, bacteria, or fungi). The burden of cardiovascular disease, particularly hypertension, leading to stroke, heart and kidney failures, cardiomyopathies and coronary heart disease, is also increasing rapidly in LMICs and is now a major public health problem in Africa. The project will explore how the 3 KETs can be used for both wide screening and for improving patients' capability to self-manage their condition, with an augmented interpretation of symptoms and signs. The project has two main goals: prevention (e.g., supporting wide screening of diseases) and to empower patients' capability to manage their health conditions.

This interdisciplinary PhD project combines engineering, biology and medicine for which the candidate will receive multidisciplinary training in quantitative skills (e.g., AI, signal processing, statistical analysis), applied anatomy, biology and physiology and ethical and regulatory competences.