Web Mining and Anemia Classification in Gujarat via WWW

Abstract

Web mining makes extracting internet data from big databases feasible. Low hemoglobin or insufficient red blood cells are symptoms of anemia. Undernutrition is the most common cause, and it is most common in young children, pregnant women, and women of childbearing age. If it is not treated or doesn't take into consideration, it could lead to an enlarged heart or heart failure. In this study, we gather data from the web about anemia in Gujarat and categorize it in various ways based on its parameter. The dataset builds from web scrapping using Python soup. The dataset we extract can be further classified to make a decision. This research helps in identifying anemia-related information as well as saving lives. Data mining tools predict future trends, help organizations, and present knowledge in the form of the easiest way so that humans can understand. The data can be processed, analyzed, and presented by a specifically trained algorithm for diverse stakeholders, including policymakers, program planners, health service providers, academicians, research scholars, and common citizens, enabling them for evidence-based, data-driven decision-making