To Predict The Best Hospital In An Area Using Machine Learning

Abstract

In health care sector, we have enormous demand of best Medicare for the patients. Now how to choose the best hospital for the patient among various hospitals in an area? The KNN supervised machine learning approach is used to predict the best hospital for the patient on the basis of various attributes used in the dataset. The various distance measure methods are used to calculate the similarity between attributes. The method like KNN with Euclidean, Manhattan and Minkowski distances is used to measure the similarity among the attributes. However Euclidean distance have limitation in a real data set which often have some degree of covariance and it does capitalize on any statistical regularities in the data that might estimated from a large training set of labeled data. In this paper, we use the KNN to choose the optimal hospital for the patients on the basis of cost and quality variables. The K-nearest neighbor method of supervised machine learning is used to predict which hospital is optimal for the patient according to need of patients. The attributes type of hospital, surroundings, near to hospital determines the cost factor. And the modern equipments, specialist doctors, medical staff quality determines the quality Factor.