29/06/2025
Last week, I was privileged to attend ALLSTAR Artificial Intelligence (AI) and Machine Learning (ML) in Tuberculosis (TB) research (23rd–27th June at RAN, Kololo) organised by University of Georgia,USA, Makerere and Mbarara Universities.
The ALLSTAR intense short course attracted over 470 applicants from various fields, but only 35 were selected. We were honoured to have highly experienced, top-notch international and local experts led by Prof. Noah Kiwanuka, Prof Juliet Ssekandi, Dr Jin Sun, Tianming Liu, among others.
•We were equipped with practical skills in key AI and machine learning areas, ranging from data management and model evaluation to computer vision, large language models, and ethical considerations in digital health.
•I learnt how cell phone network/data (CDR) can be used to track the spread of infectious diseases like TB to foster timely treatment and prevent or contain outbreaks—this is easier with AI.
•Adherence to drugs can improve by Video Directly Observed Therapy (VDOT), where a patient takes medicines as selfie video goes direct to health workers in real time. AI simplifies video review, reducing health worker fatigue and burnout.
•In addition to what I learnt in AI summit at Speke Resort, Munyonyo sponsored by UCC, I learnt more on how exactly machines learn and algorithms used like Decision tree, Linear regression, Logistic regression and supportive vector machine.
We also covered topics such as Deep Neural Networks, big data and data quality, computer vision (labelling and annotations), LLMs (GPTs and BERT)—how they are simplifying research performing week's tasks in less than 5 minutes.
Bonus:
In future, I will be able to stay at home and perform surgeries remotely hundreds of miles away. This will increase access to healthcare, especially in rural areas, since 70% of all doctors in Uganda are in urban areas.
