Healthcare Vulnerability Mapping Using K- means++ Algorithm and Entropy Method
Vulnerable population in healthcare refer to those who are at greater risk of suffering from health hazards due to various socio-economic factors, geographical barriers and medical conditions. Mapping of this vulnerable population is a vital part of healthcare planning for any region. Results of vulnerability mapping later can help with meaningful interventions for healthcare demands.
This study focuses on combining geo analytics, unsupervised machine learning algorithm and entropy method for performing vulnerability mapping based on various above- mentioned factors.