Spatial Mapping and Prediction of Diphtheria Risk in Surabaya, Indonesia, Using the Hierarchical Clustering Algorithm

Efficient ensemble machine learning techniques for early prediction of diphtheria diseases based on clinical data

“…Fariza et al [27] used the hierarchical clustering method to provide a new method to diphtheria risk analysis in Surabaya based on multiple parameters, including (Diphtheria, Tetanus Pertussis) immunization, number of diphtheria sufferers, and population density. The 2019 predictions reveal that using a single linkage rather than an average or complete linkage resulted in a lower diphtheria risk level of susceptibility with the least variance of 4.43 10-5.…”