🎓 Upcoming SSACAB Biostatistics Seminar Series
#SSACAB
|
#Scienceforafricafoundation
|
#Wellcometrust
|
#Biostatistics
|
#MachineLearning
|
#MetaAnalysis
|
#PublicHealth
|
#DataScience
|
#HealthResearch
|
#StrokeResearch
|
#Epidemiology
|
#ResearchExcellence
|
#CapacityStrengthening
|
#UniversityOfMalawi
|
#AfricanResearch
|
#EvidenceBasedResearch
|
#PredictiveAnalytics
|
#GlobalHealth
|
#SSACABSeminarSeries
Join us for an engaging seminar featuring Tiwonge Martha Lungu (MSc in Biostatistics) and Memory Makuta (MSc in Biostatistics) from the University of Malawi, who will share their research on the application of advanced statistical methods to address important public health and methodological challenges.
📊 Machine Learning Approach to Predict Risk Factors of Stroke in Malawi
Presenter: Tiwonge Martha Lungu
This presentation will explore the use of machine learning techniques to identify major stroke risk factors within the Malawian population, compare predictive models, and evaluate their performance using key predictive metrics.
Why this matters:
Stroke is a leading cause of disability and death worldwide. Improved risk prediction can support earlier interventions, targeted prevention strategies, and more effective healthcare planning, particularly in low-resource settings.
🔬 Evaluation of Model Diagnostic Methods in Random-Effects Meta-Analysis: A Simulation Study
Presenter: Memory Makuta
This presentation will examine methods for detecting outlying and influential studies in random-effects meta-analysis, evaluate their performance through simulation studies, and demonstrate their application using DHS data on child stunting in sub-Saharan Africa.
Why this matters:
Meta-analyses play a critical role in informing research, policy, and practice. Identifying the most reliable diagnostic methods helps strengthen the quality of evidence used to guide public health decisions and interventions.