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X-ray image classification using Deep Learning method for Covid-19 diagnostic

Published: 26 November 2021 Publication History

Abstract

Recently, the World Health Organization (WHO) was identified Coronavirus COVID 19 as a worldwide epidemic, usage the techniques for early diagnosis of disease gives fast and correct results, the machine Learning considered the current state-of-the-art image classification technique as a new research subject in an extensive variety of academic and industrial IT, particularly in healthcare. The Deep learning classification revolution is reshaping modern healthcare systems by integrating technological. This paper presents an integrated Deep learning using Dataset of X-ray image for classification of COVID-19, In order to have an early diagnosis, nursing patients, and practicing distinct protocols after patient recovery.

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Cited By

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  • (2023)Design of an Efficient Deep Learning Framework for Covid-19 Image Classification2023 International Conference on New Frontiers in Communication, Automation, Management and Security (ICCAMS)10.1109/ICCAMS60113.2023.10525806(1-4)Online publication date: 27-Oct-2023
  • (2022)Deep Learning Models for the Diagnosis and Screening of COVID-19: A Systematic ReviewSN Computer Science10.1007/s42979-022-01326-33:5Online publication date: 25-Jul-2022

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cover image ACM Other conferences
NISS '21: Proceedings of the 4th International Conference on Networking, Information Systems & Security
April 2021
410 pages
ISBN:9781450388719
DOI:10.1145/3454127
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 26 November 2021

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Author Tags

  1. COVID 19
  2. Deep Learning
  3. Who
  4. X-Ray

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  • (2023)Design of an Efficient Deep Learning Framework for Covid-19 Image Classification2023 International Conference on New Frontiers in Communication, Automation, Management and Security (ICCAMS)10.1109/ICCAMS60113.2023.10525806(1-4)Online publication date: 27-Oct-2023
  • (2022)Deep Learning Models for the Diagnosis and Screening of COVID-19: A Systematic ReviewSN Computer Science10.1007/s42979-022-01326-33:5Online publication date: 25-Jul-2022

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