UGC Approved Journal no 63975(19)

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Published in:

Volume 7 Issue 12
December-2020
eISSN: 2349-5162

UGC and ISSN approved 7.95 impact factor UGC Approved Journal no 63975

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Published Paper ID:
JETIR2012290


Registration ID:
304634

Page Number

674-679

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Title

Detection and Prediction Analysis of Featured Dataset of Infectious Diseases in Context of IoT: A Review

Authors

Abstract

Infection occurs due to pathogenic microorganisms such as bacteria, viruses, parasites and fungi. The disease spreads directly or indirectly from one person to another. The key part of this work resides in the weight and significance review for evaluating the infectious disease of each clinical parameter. There is, however, no parameter or parameters with limited effect in classification that is too distinct from the remainder. However, this research also noticed that the heartbeat may have a strong influence as part of a potential infectious mechanism for classification of an input sample. In addition, this paper also tested that in the majority of instances the acute respiratory infection is well established than the other two. In order to ensure optimal efficiency of the machine learning models, the next study recommendation is to expand the sample data base scale. Minor injuries can affect rest and home care, but some life-threatening injuries may require hospitalization. This vaccine can prevent many infections such as measles and water. Washing your hands well will help prevent most infections. The Internet of Things is perhaps today's most exciting technology problems. Several industry analysts say there have been estimates of more than 20 billion wired apps. Smartphones, handheld devices and other devices are around us and all use sensors. Today's devices play a huge part in our daily lives and the Internet of Things. This paper explores the detection and prediction Analysis of Featured Dataset of Infectious Diseases. Also, investigation initiated for the scope of the research for the IoT platform usability.

Key Words

Infectious Diseases, Featured Dataset, Prevention Mechanisms

Cite This Article

"Detection and Prediction Analysis of Featured Dataset of Infectious Diseases in Context of IoT: A Review ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.7, Issue 12, page no.674-679, December-2020, Available :http://www.jetir.org/papers/JETIR2012290.pdf

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2349-5162 | Impact Factor 7.95 Calculate by Google Scholar

An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 7.95 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator

Cite This Article

"Detection and Prediction Analysis of Featured Dataset of Infectious Diseases in Context of IoT: A Review ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.7, Issue 12, page no. pp674-679, December-2020, Available at : http://www.jetir.org/papers/JETIR2012290.pdf

Publication Details

Published Paper ID: JETIR2012290
Registration ID: 304634
Published In: Volume 7 | Issue 12 | Year December-2020
DOI (Digital Object Identifier):
Page No: 674-679
Country: Delhi, Delhi, India .
Area: Engineering
ISSN Number: 2349-5162
Publisher: IJ Publication


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