Using Machine Learning to Predict Cancer Rates in Mongolia Over the Past Five Years

The study describes the cancer incidence in Mongolia in the last five years, using machine learning cluster analysis to classify and calculate the different groups of aimags, capital cities, and regions. The study data includes the incidence data of 21 aimags and capital cities in accordance with the zoning of Mongolia in the last 5 years. When the data was divided into 10 clusters using machine learning cluster analysis, the incidence in clusters 3 and 5 was found to have similar values and was regionally related. The provinces in cluster 8 have similar incidence rates and appear regionally dependent. Therefore, we can propose and apply this research work to develop an assessment model that can be used by medical workers, decision-makers in the field and researchers to create a disease assessment with regional, local, provinces, and capital city classifications, and to monitor and evaluate activities.