Implementation of Child Healthcare System by Using Machine Learning Techniques

Abstract

The focus of the article was paediatric healthcare for children under the age of five. This approach was designed with the goal of tracking children's development from infancy to age five. The goal of the child healthcare system is to provide treatment for growing children outside of hospitals. Nowadays, because we live in a purely digital age, we can provide parents the ability to monitor their child's development while they remain in their own country. Children's info can be uploaded by their parents.  The system can then assess the present development and growth status, spot unhealthy behaviours, anticipate potential chronic diseases, report health-related factors (such as vaccination coverage) that's in the immediate surroundings, and finally offer tailored solutions to avert health hazards as quickly as possible. The studies included in this study concentrate on utilising machine learning algorithms to forecast child healthcare. We put the system into practise using a decision tree for CHS, MySQL for reminders about immunizations, and the K-means Elbow technique for maternal registration and notification.