CLASSIFICATION AND ANALYSIS OF BIGDATA USING HOSPITAL APPOINTMENT PREDECTION SYSTEM

1*G. Adi Narayana, S. Stewart Kirubakaran

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Abstract:

The high percentage of patients missing their appointment, be it a consultation or a medical examination, is a recurrent issue in healthcare. The present study seeks behavioral trends for patients that allow predicting the probability of no-shows. We are investigating the ease of using Machine Learning models to perform this function This research includes the exploratory data analysis of the 100k medical appointments in Brazil and focuses on whether or not patients are turning up for appointments. Data cleaning / preparation and data analysis will be performed on the whole data collection to evaluate the data validity. For every two variables, Calculate the percentages of combinations of groups to classify the largest number of patients who did not turn up. The purpose of this study is to serve as a starting point for identifying the factors that can contribute to the patients who miss their appointments. In addition, comparing and discussing the performance of comparative analysis with finding the best accuracy is applied by given dataset attributes in different supervised machine learning techniques from the data set with Interface based application.

Keywords:

appointment, examination, comparing and discussing, combinations, attributes

Paper Details
Month3
Year2020
Volume24
IssueIssue 3
Pages4045-4050