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  → A Comparative Evaluation of Kaplan-Meier, Cox Proportional Hazards, and Random Survival Forests for Neonatal Mortality Prediction
  
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  → Evaluating the Performance of Ensemble and Single Classifiers with Explainable Artificial Intelligence (XAI) on Hypertension Risk Prediction
  
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  → An Explainable AI Framework for Neonatal Mortality Risk Prediction in Kenya: Enhancing Clinical Decisions with Machine Learning
  
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  → Integrating Explainable Machine Learning Models for Early Detection of Hypertension: A Transparent Approach to AI-Driven Healthcare
  
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  → Mitigating Demographic Bias in ImageNet: A Comprehensive Analysis of Disparities and Fairness in Deep Learning Models
  
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  → Statistical Modelling of Staff Survival Time in Service at Chuka University.
  
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  → Time Series Modeling of National Hospital Insurance Fund Coverage in Kenya
  
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  → Effect of Short-Term Capital Flows on Real Exchange Rate in Kenya.
  
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  → Forecasting Outpatient Visits at Marimanti Level 4 Hospital: Time Series Analysis Using Sarima Model
  
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  → A Machine Learning Approach for Prediction of Surgical Outcomes in Elective Surgery.
  
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  → Analyzing the determinants and extent of crop diversification among smallholder coffee farmers in Kirinyaga central and east sub-counties, Kirinyaga County, Kenya.
  
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  → Comparative Analysis of Cross-Validation Techniques: LOOCV, K-folds Cross-Validation, and Repeated K-folds Cross-Validation in Machine Learning Models
  
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  → Evaluating the Performance of Ensemble and Single Classifiers with Explainable Artificial Intelligence (XAI) on Hypertension Risk Prediction
  
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  → Explainable Artificial Intelligence Models for Predicting Malaria Risk in Kenya