Smart material process in additive healthcare manufacturing

Abstract

Healthcare system takes challenges in making an effort for the patients and individuals in providing a better diagnosis. Since there are huge volumes of healthcare data are available, the analysis of this data depends upon the collection and integration from various resources. In order to diagnosis the diseas-es people spend a lump sum amount which is not affordable by all, with the help of the data explosion and with the power of data analytics and machine learning. A robust and a powerful data model are built to identify the cluster the population on various criteria's. The category of diseases that they might encounter in the near future is predicted using the data. It can also prescribe the respective diagno-sis that they can afford and take necessary action before in hand. This will be useful in discovering the cause of the disease and to alert them with respective dis-coveries. By defining the business problem and mapping to suitable algorit hms such as NN, SVM, KNN, Navies Bayes' and logistic regression with respective data points and EDA is prepared. The curated data have been used to support a number of healthcare analytic applications, including descriptive analytics, data visualization, p atient stratification, and predictive modelling.