A Study on Techniques for Diabetes Prediction model using Machine Learning: Improving Healthcare Through Artificial Intelligence and Machine Learning (Journal of Advances and Scholarly Researches in Allied Education, 2020)
The aim of this study is to the using Artificial Intelligence and machine learning in healthcareis a recent research field. In this area of research, Artificial Intelligence and machine learning forhealthcare such as Treatment efficiency, Healthcare management, Fraud and abuse detection, analyzingthe behavior of patients, Customer relationship management, etc. is already done. This research isintended to propose an Artificial Intelligence and machine learning model for healthcare, finding thequalitative attributes of patients, preparation of dataset for mining and diagnosis of diabetes byArtificial Intelligence and machine learning to improve the treatment effectiveness which will save thetime and enhance the same for faster treatment and analysis. The researcher has studied the existingsystem and its problem is being identified. The researcher has provided an appropriate ArtificialIntelligence and machine learning model for diabetic healthcare. Medical field faces new difficulties likenew diseases, cost, new therapeutics, fast decisions etc. Since medical decision making demandsutmost accuracy of diagnosis, it is a tedious, demanding and challenging task for physicians. Anautomated system which helps in disease diagnosis, prognosis, which will benefit the medical. This hasattracted researchers to design medical decision support systems with utmost accuracy.Numerous datascience applications are found in the clinical related regions, for example, Medical gadget industry,Hospital Management and Pharmaceutical Manufacturing. Data science realistic in social insuranceindustry assumes a significant job in identification and analysis of the diseases. The individualexamination will locate the most helpful and concealed information from the dataset, and structure theprescient model. This is the reason behind the use of data science. Famously data science hastremendous application regions in the human services area. Data science can either be utilized foranalysis, for example, pattern-identification, testing of hypothesis, risk evaluation or forecast, forexample, AI models that make appropriate expectations that are the probability of an occasionhappening later on, in light of known information factors.