Ensembling of Efficient Deep Convolutional Networks and Machine Learning Algorithms for Resource Effective Detection of Tuberculosis Using Thoracic (Chest) Radiography-Reference-Cited by-同舟云学术

Ensembling of Efficient Deep Convolutional Networks and Machine Learning Algorithms for Resource Effective Detection of Tuberculosis Using Thoracic (Chest) Radiography

Published:2022 Issue: Volume:10 Page:85442-85458
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Mehrrotraa Rajat¹^ORCID,Ansari M. A.²,Agrawal Rajeev³^ORCID,Tripathi Pragati²,Bin Heyat Md Belal⁴^ORCID,Al-Sarem Mohammed⁵,Muaad Abdullah Yahya Mohammed⁶^ORCID,Nagmeldin Wamda Abdelrahman Elhag⁷,Abdelmaboud Abdelzahir⁸,Saeed Faisal⁹

Affiliation:

1. Department of Electrical and Electronics Engineering, G. L. Bajaj Institute of Technology & Management, Greater Noida, India

2. Department of Electrical Engineering, School of Engineering, Gautam Buddha University, Greater Noida, India

3. Department of Computer Science, Lloyd Institute of Engineering & Technology, Greater Noida, India

4. IoT Research Center, College of Computer Science and Software Engineering, Shenzhen University, Shenzhen, China

5. College of Computer Science and Engineering, Taibah University, Medina, Saudi Arabia

6. Department of Studies in Computer Science, University of Mysore, Manasagangothri, Mysuru, India

7. Department of Information Systems, College of Computer Engineering and Sciences, Prince Sattam bin Abdulaziz University, Al-Kharj, Saudi Arabia

8. Department of Information Systems, King Khalid University, Muhayel Aseer, Saudi Arabia

9. Department of Computing and Data Science, DAAI Research Group, School of Computing and Digital Technology, Birmingham City University, Birmingham, U.K.

Funder

Deanship of Scientific Research at King Khalid University for funding this work through Large Groups

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Engineering,General Materials Science,General Computer Science,Electrical and Electronic Engineering

Link

http://xplorestaging.ieee.org/ielx7/6287639/9668973/09841572.pdf?arnumber=9841572

Reference52 articles.

1. Deep Learning Enables Accurate Diagnosis of Novel Coronavirus (COVID-19) With CT Images

2. Rethinking Computer-Aided Tuberculosis Diagnosis

3. Cross-Population Train/Test Deep Learning Model: Abnormality Screening in Chest X-Rays

4. Efficient Deep Network Architectures for Fast Chest X-Ray Tuberculosis Screening and Visualization

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