Improved Health Care Diagnostic and Preventative System Using Artificial Intelligence Approach

Abstract

The data health organizations generate is so large and complex that it can be difficult to analyze to make important decisions about patient health. These data contain detailed information about hospitals, patients, medical claims, treatment costs, and more. Therefore, there is a need to generate a powerful tool to analyze and extract important information from these complex data. Machine learning (ML) in clinical benefits is one of the most exciting areas of investigation. Machine learning plays an important role in spotting new trends in healthcare organizations, which in turn is useful to others related to the field. It is a subfield of software engineering that uses existing data in different databases to transform it into new research findings. The aim of this research is to help physicians use a tool to quantify health disorders through medical data that can be implemented in a computer-aided system. Computer-aided assessments are always faster than manual processes and provide physicians with additional resources for diagnosis and treatment. The proposed method defines specific patterns of disease in health using machine learning techniques. Compared with other existing algorithms, the proposed Improved Healthcare Prediction Using Artificial Intelligence Method (IHPAI) system yields higher efficiency in predicting healthcare-related diseases.