The Future of Child Welfare: Predictive Analytics Insights

Abstract

When the availability of data is continuously growing, predictive analytics has emerged as progressively important instrument for the provision of child health services and the implementation of child protection measures. This cutting-edge technology makes use of data gathered from prior occurrences in order to forecast future patterns and results. As a result, child welfare groups are able to make more informed judgments regarding how to provide the best possible service to their clients. Nevertheless, like any new data-driven technology, predictive analytics needs to be utilized in a responsible manner in order to guarantee that operations are both productive and ethical. Artificial Intelligence(AI) and Machine Learning(ML) have developed & increasingly widespread in modern years, which has managed to an increase in the significance of healthcare forecasting in the healthcare industry. In addition, forecasting in the healthcare industry can be utilized to enhance both the precision and the speed of diagnosis. Physicians and other medical personnel are able to identify and treat patients more promptly and effectively when they are able to anticipate possible medical events. The outcomes for patients may improve as a consequence of this, and it may even contribute to cost savings. The modeling of human cognition made possible by these technologies not only offers considerable therapeutic aid but also has the ability to diagnose disorders. The purpose of the papers that are included in this work is to make predictions about the healthcare of children by utilizing machine learning techniques. Database management system MySQL is used to keep track of vaccination facts, while Decision Tree is used to make predictions about diseases. In order to provide assistance to parents in their efforts to heal their children, the framework was developed.