Employing (Home) Organisation: MRC Unit The Gambia at London School of Hygiene and Tropical Medicine
Project title: Using artificial intelligence to improve diagnosis and long-term post-tuberculosis respiratory outcomes in children and adolescents
Dr Esin Nkereuwem is a clinical researcher at the MRC Unit The Gambia at LSHTM, with training and research experience in childhood tuberculosis, post-TB lung disease, and paediatric respiratory health. His doctoral work examined the long-term respiratory consequences of pulmonary tuberculosis in Gambian children and adolescents. Inspired by the need to improve outcomes for children surviving TB, he is developing context-appropriate clinical, radiological, and AI-enabled tools to strengthen diagnosis, follow-up care, and long-term respiratory assessment in African settings.
Summary of Project Destination
Post-tuberculosis lung disease is becoming increasingly apparent as an important child health challenge in low- and middle-income countries, where many children and adolescents experience persistent respiratory problems after completing tuberculosis treatment. However, practical tools for detecting, monitoring, and risk-stratifying post-TB lung disease in African settings remain limited. Through the AREF Fellowship, Dr Esin Nkereuwem will examine whether AI-enabled clinical and radiological tools can improve detection and longitudinal follow-up of post-TB lung disease in children and adolescents, using clinical assessment, lung function testing, and chest imaging analysis. After the Fellowship, he will develop larger implementationfocused studies to inform context-appropriate diagnosis, follow-up care, and management strategies, with the goal of strengthening childhood TB recovery pathways and improving long-term respiratory outcomes across African health systems.
Summary of Fellowship Plan
I will be based at Imperial College London under the mentorship of Dr Mitch Chen, where I will gain hands-on training in advanced approaches for analysing clinical, radiological, longitudinal, and AI-generated data relevant to post-TB lung disease. I will strengthen my skills in integrating lung function, imaging, and respiratory health data. After the Fellowship, my home institution, MRC Unit The Gambia at LSHTM, will support me to apply, share, and sustain these skills within ongoing child lung health and tuberculosis research.y applying the expertise gained during placement.
Quote
“ This Fellowship will help me turn advanced AI and respiratory research skills into better detection, follow-up, and care for African children surviving tuberculosis ”
Proposed start date of the Fellowship is October 2026