Data Mining and Its Effective Role in the Fight Against Diseases and Determine the Causal Relationship

Abstract

Health data is complex, huge and heterogeneous data, so it is difficult to analyze it by traditional methods, especially as it is data based on tracking and investigation, especially in the field of chronic diseases, where the investigation of the history of the sick person and the history of the social relations associated with him requires investigation.

On the other hand, data mining in the field of non-communicable diseases is the main support for the task of knowledge extraction as this study aims to assess the current state of knowledge in data mining techniques that will help in preventing and diagnosing non-communicable diseases. To achieve the goal of the study, the researcher used a critical evaluation approach. By reviewing the theoretical literature and previous studies related to the subject of the study, it also aimed to identify the objectives pursued by the studies, results, and recommendations, and to indicate aspects of agreement and differences in light of the data.

The current research has reached several results, the most prominent of which is that the health field really needs to search for data due to the tremendous growth of electronic health records. The tools used in data exploration have varied and varied, and the technical systems have also varied. The paper also concluded that the focus of recent studies has been on research in Data mining techniques used to prevent outbreaks of chronic and non-infectious diseases such as heart disease, diabetes and stroke, and that data mining science needs more recent studies because developments in the health field are accelerating and discoveries are successive and on the other hand we notice the spread of some diseases more than before, so the medical field needs For more research on modern techniques to confront and combat infectious and non-communicable diseases as well.