A Systematic Review of AI Privileges to Combat Widen Threat of Flavivirus

Title

A Systematic Review of AI Privileges to Combat Widen Threat of Flavivirus

Creator

Potluri S.; Satpathy S.; Mahapatra S.; Nanjundan P.; Mohanty S.N.

Description

In order to prevent the extraordinary spread of sickness caused by Flavivirus, the healthcare business as well as public health are working tirelessly. Individual lives have been affected, but mosquito-infested public locations have made a considerable influence on the general publics health. Site adaptability, climate change, and inadequate healthcare services and surveillance all contribute to the spread of the virus. The potential dangers of this virus, on the other hand, have been uncovered through extensive and ongoing research in the healthcare business. Modern healthcare facilities may benefit from the reasoning capabilities and ever-evolving analysis techniques provided by artificial intelligence. More conclusive findings have been demonstrated in the realm of AI applications in healthcare domains such as cancer, neurology, and cardiology. A number of research works have justified the use of AI-oriented algorithms for intelligently handling unstructured and huge healthcare data. When it comes to using artificial intelligence (AI) to identify, forecast, diagnose, and treat disease using data from public health and biological databases, the current effort aims to undertake an extensive examination. There may be issues in integrating assistive technology into the current healthcare system, as well. Because of this review, we hope that by merging AI research with clinical and public health specialists, critical knowledge may be extracted from data in order to unchain the relevant information of Flavivirus disease from its chains. 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

Source

Smart Innovation, Systems and Technologies, Vol-317, pp. 189-199.

Date

2023-01-01

Publisher

Springer Science and Business Media Deutschland GmbH

Subject

Artificial intelligence; Ensemble classifier; Flavivirus; Healthcare; Machine learning; Prediction

Coverage

Potluri S., Department of CSE, Faculty of Science and Technology, IcfaiTech, ICFAI Foundation for Higher Education, Donthanpally, Shankarpalli Road, Telangana, Hyderabad, 501203, India; Satpathy S., Faculty of Emerging Technologies, Sri Sri University, Odisha, Cuttack, 751002, India; Mahapatra S., Department of Computer Application, Institute of Technical Education and Research, Siksha O Anusandhan Deemed to be University, Bhubaneswar, 751030, India; Nanjundan P., Department of Data Science, CHRIST University, Pune, Lavasa, India; Mohanty S.N., Vardhaman College of Engineering (Autonomous), Telangana, Hyderabad, 501218, India

Rights

Restricted Access

Relation

ISSN: 21903018; ISBN: 978-981196067-3

Format

Online

Language

English

Type

Conference paper

Identifier

https://doi.org/10.1007/978-981-19-6068-0_18

https://www.scopus.com/inward/record.uri?eid=2-s2.0-85145007216&doi=10.1007%2f978-981-19-6068-0_18&partnerID=40&md5=90c4962cd944cee8e49bf1a7748b0fa4