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

Journals

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  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
  116. CİVİL D, OZTİMUR KARADAG O. X-RAY GÖĞÜS GÖRÜNTÜLERİNİN GÖRÜNTÜ DÖNÜŞTÜRÜCÜLER İLE SINIFLANDIRILMASI VE COVİD-19 TESPİTİ. Uludağ University Journal of The Faculty of Engineering 2023:349 View
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  118. Tan M, Xia J, Luo H, Meng G, Zhu Z. Applying the digital data and the bioinformatics tools in SARS-CoV-2 research. Computational and Structural Biotechnology Journal 2023;21:4697 View
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  120. Xie P, Zhao X, He X. Improve the performance of CT-based pneumonia classification via source data reweighting. Scientific Reports 2023;13(1) View
  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
  124. Farhat F, Sohail S, Alam M, Ubaid S, Shakil , Ashhad M, Madsen D. COVID-19 and beyond: leveraging artificial intelligence for enhanced outbreak control. Frontiers in Artificial Intelligence 2023;6 View
  125. Hao Y, Zhang C, Li X. DBM-ViT: A multiscale features fusion algorithm for health status detection in CXR / CT lungs images. Biomedical Signal Processing and Control 2024;87:105365 View
  126. Ahmad I, Merla A, Ali F, Shah B, AlZubi A, AlZubi M. A deep transfer learning approach for COVID-19 detection and exploring a sense of belonging with Diabetes. Frontiers in Public Health 2023;11 View
  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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  133. Zhang Y, Pei Y, Górriz J. SCNN: A Explainable Swish-based CNN and Mobile App for COVID-19 Diagnosis. Mobile Networks and Applications 2023 View
  134. Mehrdad S, Shamout F, Wang Y, Atashzar S. Deep learning for deterioration prediction of COVID-19 patients based on time-series of three vital signs. Scientific Reports 2023;13(1) View
  135. Sreelakshmi S, Anoop V. A deep convolutional neural network model for medical data classification from computed tomography images. Expert Systems 2023 View
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  139. Nur-A-Alam M, Nasir M, Ahsan M, Based M, Haider J, Kowalski M. Ensemble classification of integrated CT scan datasets in detecting COVID-19 using feature fusion from contourlet transform and CNN. Scientific Reports 2023;13(1) 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