A Study on Techniques for Diabetes Prediction model using Machine Learning | Original Article

ABSTRACT:

The aim of this study is to the using Artificial Intelligence and machine learning in healthcare is a recent research field. In this area of research, Artificial Intelligence and machine learning for healthcare such as Treatment efficiency, Healthcare management, Fraud and abuse detection, analyzing the behavior of patients, Customer relationship management, etc. is already done. This research is intended to propose an Artificial Intelligence and machine learning model for healthcare, finding the qualitative attributes of patients, preparation of dataset for mining and diagnosis of diabetes by Artificial Intelligence and machine learning to improve the treatment effectiveness which will save the time and enhance the same for faster treatment and analysis. The researcher has studied the existing system and its problem is being identified. The researcher has provided an appropriate Artificial Intelligence and machine learning model for diabetic healthcare. Medical field faces new difficulties like new diseases, cost, new therapeutics, fast decisions etc. Since medical decision making demands utmost accuracy of diagnosis, it is a tedious, demanding and challenging task for physicians. An automated system which helps in disease diagnosis, prognosis, which will benefit the medical. This has attracted researchers to design medical decision support systems with utmost accuracy.Numerous data science applications are found in the clinical related regions, for example, Medical gadget industry, Hospital Management and Pharmaceutical Manufacturing. Data science realistic in social insurance industry assumes a significant job in identification and analysis of the diseases. The individual examination will locate the most helpful and concealed information from the dataset, and structure the prescient model. This is the reason behind the use of data science. Famously data science has tremendous application regions in the human services area. Data science can either be utilized for analysis, for example, pattern-identification, testing of hypothesis, risk evaluation or forecast, for example, AI models that make appropriate expectations that are the probability of an occasion happening later on, in light of known information factors.