This paper is in the following e-collection/theme issue:

JMIR Theme Issue: COVID-19 Special Issue (2452) Decision Support for Health Professionals (1185) Imaging Informatics (193) Machine Learning (1465) Outbreak and Pandemic Preparedness and Management (1727) Theme Issue: Novel Coronavirus (COVID-19) Outbreak Rapid Reports (1517)

Published on in Vol 22, No 6 (2020): June

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/19569, first published .
COVID-19 Pneumonia Diagnosis Using a Simple 2D Deep Learning Framework With a Single Chest CT Image: Model Development and Validation

COVID-19 Pneumonia Diagnosis Using a Simple 2D Deep Learning Framework With a Single Chest CT Image: Model Development and Validation

COVID-19 Pneumonia Diagnosis Using a Simple 2D Deep Learning Framework With a Single Chest CT Image: Model Development and Validation

Authors of this article:

Hoon Ko1 Author Orcid Image ;   Heewon Chung1 Author Orcid Image ;   Wu Seong Kang2 Author Orcid Image ;   Kyung Won Kim3 Author Orcid Image ;   Youngbin Shin3 Author Orcid Image ;   Seung Ji Kang4 Author Orcid Image ;   Jae Hoon Lee5 Author Orcid Image ;   Young Jun Kim5 Author Orcid Image ;   Nan Yeol Kim2 Author Orcid Image ;   Hyunseok Jung6 Author Orcid Image ;   Jinseok Lee1 Author Orcid Image
Article Authors Cited by (198) Tweetations (23) Metrics

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  114. Yamada A, Kamagata K, Hirata K, Ito R, Nakaura T, Ueda D, Fujita S, Fushimi Y, Fujima N, Matsui Y, Tatsugami F, Nozaki T, Fujioka T, Yanagawa M, Tsuboyama T, Kawamura M, Naganawa S. Clinical applications of artificial intelligence in liver imaging. La radiologia medica 2023;128(6):655 View
  115. Shu L, Zhong K, Chen N, Gu W, Shang W, Liang J, Ren J, Hong H. Predicting the severity of white matter lesions among patients with cerebrovascular risk factors based on retinal images and clinical laboratory data: a deep learning study. Frontiers in Neurology 2023;14 View
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  121. Talaat M, Si X, Xi J. Multi-Level Training and Testing of CNN Models in Diagnosing Multi-Center COVID-19 and Pneumonia X-ray Images. Applied Sciences 2023;13(18):10270 View
  122. Lee Y, Shin H, Kim J, Lee J. A Convolutional Neural Network for Classification of Stimuli Based on Stretchable Mechanical Sensor. IEEE Sensors Journal 2023;23(17):20338 View
  123. Santosh K, GhoshRoy D, Nakarmi S. A Systematic Review on Deep Structured Learning for COVID-19 Screening Using Chest CT from 2020 to 2022. Healthcare 2023;11(17):2388 View
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  127. Budak C, Mençik V, Varışlı O. Online diagnosis of COVID-19 from chest radiography images by using deep learning algorithms. Neural Computing and Applications 2023;35(28):20717 View
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  132. Amin J, Almas Anjum M, Gul N, Imran Sharif M, Irfan Sharif M, Kadry S. Localization model and rank-based features selection approach for the classification of GGO and consolidation stages of COVID-19. Expert Systems with Applications 2024;239:122317 View
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  145. Zaeri N. Artificial intelligence and machine learning responses to COVID-19 related inquiries. Journal of Medical Engineering & Technology 2023;47(6):301 View
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Books/Policy Documents

  1. Sugiura A. Bio-information for Hygiene. View
  2. Jayashree R. Understanding COVID-19: The Role of Computational Intelligence. View
  3. Tintín V, Florez H. Computational Science and Its Applications – ICCSA 2021. View
  4. Zaeri N. Simulation Modeling. View
  5. Gope B, Kohar R. Proceedings of Data Analytics and Management. View
  6. Escobar-Linero E, Muñoz-Saavedra L, Luna-Perejón F, Civit-Masot J, Rivas-Pérez M, Domínguez-Morales M, Balcells A. Recent Advancements in Smart Remote Patient Monitoring, Wearable Devices, and Diagnostics Systems. View
  7. Alquzi S, Alhichri H, Bazi Y. International Conference on Innovative Computing and Communications. View
  8. Kishore C, Pemula R, Vijaya Kumar S, Rao K, Chandra Sekhar S. Soft Computing: Theories and Applications. View
  9. Gurcan O, Atici U, Bicer M, Dogan O. Intelligent and Fuzzy Techniques for Emerging Conditions and Digital Transformation. View
  10. Imanov E, Lakshitha Liyanagamage V. 15th International Conference on Applications of Fuzzy Systems, Soft Computing and Artificial Intelligence Tools – ICAFS-2022. View
  11. Gunturu L, Dornadula G. Emerging Technologies During the Era of COVID-19 Pandemic. View
  12. Swapnarekha H, Behera H, Nayak J, Naik B. Computational Intelligence in Pattern Recognition. View
  13. Gunturu L, Dornadula G. Computational Intelligence for COVID-19 and Future Pandemics. View
  14. Grönvall E, Lundberg S. Pervasive Computing Technologies for Healthcare. View
  15. Hazela B, Khalid S, Asthana P. Medical Imaging and Health Informatics. View
  16. Motta P, Cesar Cortez P, Lobo Marques J. Computerized Systems for Diagnosis and Treatment of COVID-19. View
  17. Balavand A, Pahlevani S. Optimization Methods for Product and System Design. View
  18. Kumar A, Roy P, Mishra A, Das S. Big Data, Machine Learning, and Applications. View
  19. Vignesh U, Ratnakumar R. Bio-Inspired Optimization Techniques in Blockchain Systems. View