Open AccessCOVID-19 PATIENTS ANALYSIS AND RISK PREDICTION BASED ON LIFESTYLE DISEASES THROUGH INDIAN DATASET
Author(s) -
Vijaykumar Patil,
D. R. Ingle
Publication year - 2021
Publication title -
international journal of engineering applied science and technology
Language(s) - English
Resource type - Journals
ISSN - 2455-2143
DOI - 10.33564/ijeast.2021.v06i05.030
Subject(s) - chills , sore throat , medicine , pandemic , covid-19 , naive bayes classifier , disease , diabetes mellitus , artificial intelligence , infectious disease (medical specialty) , computer science , surgery , support vector machine , endocrinology
A Novel Coronavirus disease (COVID-19) is atransferable virus triggered by a recently revealedcoronavirus. World Health Organization (WHO) declaredit as pandemic worldwide. COVID-19 was originated fromWuhan, a city of China and spared over the more than 190countries over the word. The USA, Spain, Italy, Franceeven India and every country suffered a lot by thisepidemic. The indications of COVID-19 are Fever, Cough,Shortness of breath or trouble in breathing, Chills,Repeated shaking with chills, Muscle torment, Headache,Sore throat which is normal as any formal flue which eachindividual feel during season transition. In this article, thestatistical analysis like chi-square analysis, age-wise anddiseases-wise classification of recovered and deceasedpatients are performed and also the different types ofMachine Learning models like Multiple linear regression,Naive Bayes Classifier, and Multilayer PerceptronClassifier are proposed for formal analysis and riskprediction of patients with different age group andindividuals having lifestyle-based diseases with COVID-19.The dataset used for this study downloadedfrom covid19india.org, available in .csv format whichincluded travel history of patients, relation with anyexisting COVID-19 patient, and record of any lifestylebased diseases like diabetes, hypertension, respiratoryproblem, etc.