Optimizing Tuberculosis Incidence Prediction: A Systematic Review of Hybrid Modeling Approaches and Machine Learning Techniques
ABSTRACT Background Tuberculosis (TB) remains a significant global health problem, particularly in low‐ and middle‐income countries (LMICs), where accurate prediction of TB incidence is crucial for effective public health interventions. Objective This review assessed and compared statistical, machine learning (ML), and...