Statistical Explorations and Univariate Timeseries Analysis on COVID-19 Datasets to Understand the Trend of Disease Spreading and Death

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RESEARCH PRODUCT

Statistical Explorations and Univariate Timeseries Analysis on COVID-19 Datasets to Understand the Trend of Disease Spreading and Death

Santiago Martinez Ayan Chatterjee Martin Gerdes

subject

0301 basic medicine transmission rate population Severe Acute Respiratory Syndrome medicine.disease_cause lcsh:Chemical technology Biochemistry RNN Disease Outbreaks Analytical Chemistry 0302 clinical medicine Pandemic lcsh:TP1-1185 030212 general & internal medicine Instrumentation VDP::Teknologi: 500::Informasjons- og kommunikasjonsteknologi: 550 Coronavirus keras education.field_of_study public health artificial intelligence Atomic and Molecular Physics and Optics Regression machine learning Geography Severe acute respiratory syndrome-related coronavirus statistics Middle East Respiratory Syndrome Coronavirus community disease regression Coronavirus Infections LSTM Pneumonia Viral Population World Health Organization Article Betacoronavirus spread factor 03 medical and health sciences Code (cryptography)medicine Animals Humans Electrical and Electronic Engineering education Pandemics measurable sensor data algorithm SARS-CoV-2 ICD Univariate deep learning Outbreak COVID-19 medicine.disease hypothesis test python 030104 developmental biology correlation Cats Middle East respiratory syndrome Cattle Demography

description

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year	journal	country	edition	language
2020-05-01	Sensors

10.3390/s20113089 https://www.mdpi.com/1424-8220/20/11/3089

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