Day 2 of Chuka University’s Center for Data Analytics and Modeling (CDAM) workshop on “Malaria Risk Prediction in Kenya Using AI and Machine Learning Models in R” concluded with an insightful session on healthcare decision-making driven by Artificial Intelligence, emphasizing the integration of explainable AI (XAI) tools. Attendees engaged in practical exercises to predict malaria risk using diverse datasets and machine learning algorithms. The day concluded with a training evaluation, providing participants an opportunity for reflection and feedback.
Through hands-on experience with advanced analytical tools and models, participants acquired cutting-edge skills in AI and machine learning to support effective malaria risk prediction and contribute to improved healthcare outcomes in Kenya. This experience enhanced their capacity to develop data-driven solutions, strengthen public health surveillance, and make informed decisions aimed at reducing the burden of malaria in affected communities.
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