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

JMIR Theme Issue: COVID-19 Special Issue (2501) Decision Support for Health Professionals (1364) Imaging Informatics (240) Machine Learning (1772) Outbreak and Pandemic Preparedness and Management (1785) Theme Issue: Novel Coronavirus (COVID-19) Outbreak Rapid Reports (1532)

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 (206) Tweetations (23) Metrics

Journals

  1. Ozsahin I, Sekeroglu B, Musa M, Mustapha M, Uzun Ozsahin D. Review on Diagnosis of COVID-19 from Chest CT Images Using Artificial Intelligence. Computational and Mathematical Methods in Medicine 2020;2020:1 View
  2. Tayarani N. M. Applications of artificial intelligence in battling against covid-19: A literature review. Chaos, Solitons & Fractals 2021;142:110338 View
  3. Wang S, Govindaraj V, Górriz J, Zhang X, Zhang Y. Covid-19 classification by FGCNet with deep feature fusion from graph convolutional network and convolutional neural network. Information Fusion 2021;67:208 View
  4. Owais M, Arsalan M, Mahmood T, Kang J, Park K. Automated Diagnosis of Various Gastrointestinal Lesions Using a Deep Learning–Based Classification and Retrieval Framework With a Large Endoscopic Database: Model Development and Validation. Journal of Medical Internet Research 2020;22(11):e18563 View
  5. Syeda H, Syed M, Sexton K, Syed S, Begum S, Syed F, Prior F, Yu Jr F. Role of Machine Learning Techniques to Tackle the COVID-19 Crisis: Systematic Review. JMIR Medical Informatics 2021;9(1):e23811 View
  6. Yoo S, Goo J, Yoon S. Role of Chest Radiographs and CT Scans and the Application of Artificial Intelligence in Coronavirus Disease 2019. Journal of the Korean Society of Radiology 2020;81(6):1334 View
  7. Wei C. Research on university laboratory management and maintenance framework based on computer aided technology. Microprocessors and Microsystems 2020:103617 View
  8. Sitaula C, Hossain M. Attention-based VGG-16 model for COVID-19 chest X-ray image classification. Applied Intelligence 2021;51(5):2850 View
  9. Wang S, Nayak D, Guttery D, Zhang X, Zhang Y. COVID-19 classification by CCSHNet with deep fusion using transfer learning and discriminant correlation analysis. Information Fusion 2021;68:131 View
  10. Li D, Zhang Q, Tan Y, Feng X, Yue Y, Bai Y, Li J, Li J, Xu Y, Chen S, Xiao S, Sun M, Li X, Zhu F. Prediction of COVID-19 Severity Using Chest Computed Tomography and Laboratory Measurements: Evaluation Using a Machine Learning Approach. JMIR Medical Informatics 2020;8(11):e21604 View
  11. Xu M, Ouyang L, Han L, Sun K, Yu T, Li Q, Tian H, Safarnejad L, Zhang H, Gao Y, Bao F, Chen Y, Robinson P, Ge Y, Zhu B, Liu J, Chen S. Accurately Differentiating Between Patients With COVID-19, Patients With Other Viral Infections, and Healthy Individuals: Multimodal Late Fusion Learning Approach. Journal of Medical Internet Research 2021;23(1):e25535 View
  12. Elmuogy S, Hikal N, Hassan E. An efficient technique for CT scan images classification of COVID-19. Journal of Intelligent & Fuzzy Systems 2021;40(3):5225 View
  13. Ho T, Park J, Kim T, Park B, Lee J, Kim J, Kim K, Choi S, Kim Y, Lim J, Choi S. Deep Learning Models for Predicting Severe Progression in COVID-19-Infected Patients: Retrospective Study. JMIR Medical Informatics 2021;9(1):e24973 View
  14. Homayounieh F, Bezerra Cavalcanti Rockenbach M, Ebrahimian S, Doda Khera R, Bizzo B, Buch V, Babaei R, Karimi Mobin H, Mohseni I, Mitschke M, Zimmermann M, Durlak F, Rauch F, Digumarthy S, Kalra M. Multicenter Assessment of CT Pneumonia Analysis Prototype for Predicting Disease Severity and Patient Outcome. Journal of Digital Imaging 2021;34(2):320 View
  15. Abbasi W, Abbas S, Andleeb S, ul Islam G, Ajaz S, Arshad K, Khalil S, Anjam A, Ilyas K, Saleem M, Chughtai J, Abbas A. COVIDC: An expert system to diagnose COVID-19 and predict its severity using chest CT scans: Application in radiology. Informatics in Medicine Unlocked 2021;23:100540 View
  16. Rasheed J, Jamil A, Hameed A, Al-Turjman F, Rasheed A. COVID-19 in the Age of Artificial Intelligence: A Comprehensive Review. Interdisciplinary Sciences: Computational Life Sciences 2021;13(2):153 View
  17. Mohammad-Rahimi H, Nadimi M, Ghalyanchi-Langeroudi A, Taheri M, Ghafouri-Fard S. Application of Machine Learning in Diagnosis of COVID-19 Through X-Ray and CT Images: A Scoping Review. Frontiers in Cardiovascular Medicine 2021;8 View
  18. Han C, Kim M, Kwak J, Ortega-Martorell S. Semi-supervised learning for an improved diagnosis of COVID-19 in CT images. PLOS ONE 2021;16(4):e0249450 View
  19. Glangetas A, Hartley M, Cantais A, Courvoisier D, Rivollet D, Shama D, Perez A, Spechbach H, Trombert V, Bourquin S, Jaggi M, Barazzone-Argiroffo C, Gervaix A, Siebert J. Deep learning diagnostic and risk-stratification pattern detection for COVID-19 in digital lung auscultations: clinical protocol for a case–control and prospective cohort study. BMC Pulmonary Medicine 2021;21(1) View
  20. Roberts M, Driggs D, Thorpe M, Gilbey J, Yeung M, Ursprung S, Aviles-Rivero A, Etmann C, McCague C, Beer L, Weir-McCall J, Teng Z, Gkrania-Klotsas E, Ruggiero A, Korhonen A, Jefferson E, Ako E, Langs G, Gozaliasl G, Yang G, Prosch H, Preller J, Stanczuk J, Tang J, Hofmanninger J, Babar J, Sánchez L, Thillai M, Gonzalez P, Teare P, Zhu X, Patel M, Cafolla C, Azadbakht H, Jacob J, Lowe J, Zhang K, Bradley K, Wassin M, Holzer M, Ji K, Ortet M, Ai T, Walton N, Lio P, Stranks S, Shadbahr T, Lin W, Zha Y, Niu Z, Rudd J, Sala E, Schönlieb C. Common pitfalls and recommendations for using machine learning to detect and prognosticate for COVID-19 using chest radiographs and CT scans. Nature Machine Intelligence 2021;3(3):199 View
  21. Ghaderzadeh M, Asadi F, Maietta S. Deep Learning in the Detection and Diagnosis of COVID-19 Using Radiology Modalities: A Systematic Review. Journal of Healthcare Engineering 2021;2021:1 View
  22. Chung H, Ko H, Kang W, Kim K, Lee H, Park C, Song H, Choi T, Seo J, Lee J. Prediction and Feature Importance Analysis for Severity of COVID-19 in South Korea Using Artificial Intelligence: Model Development and Validation. Journal of Medical Internet Research 2021;23(4):e27060 View
  23. Moezzi M, Shirbandi K, Shahvandi H, Arjmand B, Rahim F. The diagnostic accuracy of Artificial Intelligence-Assisted CT imaging in COVID-19 disease: A systematic review and meta-analysis. Informatics in Medicine Unlocked 2021;24:100591 View
  24. Adamidi E, Mitsis K, Nikita K. Artificial intelligence in clinical care amidst COVID-19 pandemic: A systematic review. Computational and Structural Biotechnology Journal 2021;19:2833 View
  25. Helwan A, Ma’aitah M, Hamdan H, Ozsahin D, Tuncyurek O, Bangyal W. Radiologists versus Deep Convolutional Neural Networks: A Comparative Study for Diagnosing COVID-19. Computational and Mathematical Methods in Medicine 2021;2021:1 View
  26. Alhasan M, Hasaneen M. Digital imaging, technologies and artificial intelligence applications during COVID-19 pandemic. Computerized Medical Imaging and Graphics 2021;91:101933 View
  27. Athavale A, Hart P, Itteera M, Cimbaluk D, Patel T, Alabkaa A, Arruda J, Singh A, Rosenberg A, Kulkarni H. Development and Validation of a Deep Learning Model to Quantify Interstitial Fibrosis and Tubular Atrophy From Kidney Ultrasonography Images. JAMA Network Open 2021;4(5):e2111176 View
  28. Kumar V, Singh D, Kaur M, Damaševičius R. Overview of current state of research on the application of artificial intelligence techniques for COVID-19. PeerJ Computer Science 2021;7:e564 View
  29. Rehouma R, Buchert M, Chen Y. Machine learning for medical imaging‐based COVID‐19 detection and diagnosis. International Journal of Intelligent Systems 2021;36(9):5085 View
  30. Santosh K, Ghosh S. Covid-19 Imaging Tools: How Big Data is Big?. Journal of Medical Systems 2021;45(7) View
  31. Oyelade O, Ezugwu A, Chiroma H. CovFrameNet: An Enhanced Deep Learning Framework for COVID-19 Detection. IEEE Access 2021;9:77905 View
  32. Kato S, Ishiwata Y, Aoki R, Iwasawa T, Hagiwara E, Ogura T, Utsunomiya D. Imaging of COVID-19: An update of current evidences. Diagnostic and Interventional Imaging 2021;102(9):493 View
  33. Arora V, Ng E, Leekha R, Darshan M, Singh A. Transfer learning-based approach for detecting COVID-19 ailment in lung CT scan. Computers in Biology and Medicine 2021;135:104575 View
  34. CANBAY Y, İSMETOĞLU A, CANBAY P. COVİD-19 HASTALIĞININ TEŞHİSİNDE DERİN ÖĞRENME VE VERİ MAHREMİYETİ. Mühendislik Bilimleri ve Tasarım Dergisi 2021;9(2):701 View
  35. Dey S, Bhattacharya R, Malakar S, Mirjalili S, Sarkar R. Choquet fuzzy integral-based classifier ensemble technique for COVID-19 detection. Computers in Biology and Medicine 2021;135:104585 View
  36. Rahman M, Nooruddin S, Hasan K, Dey N. HOG + CNN Net: Diagnosing COVID-19 and Pneumonia by Deep Neural Network from Chest X-Ray Images. SN Computer Science 2021;2(5) View
  37. Hasan N. A Hybrid Method of Covid-19 Patient Detection from Modified CT-Scan/Chest-X-Ray Images Combining Deep Convolutional Neural Network And Two- Dimensional Empirical Mode Decomposition. Computer Methods and Programs in Biomedicine Update 2021;1:100022 View
  38. Karthik R, Menaka R, Hariharan M, Kathiresan G. AI for COVID-19 Detection from Radiographs: Incisive Analysis of State of the Art Techniques, Key Challenges and Future Directions. IRBM 2022;43(5):486 View
  39. Wang S, Satapathy S, Anderson D, Chen S, Zhang Y. RETRACTED: Deep Fractional Max Pooling Neural Network for COVID-19 Recognition. Frontiers in Public Health 2021;9 View
  40. Liu J, Zhao J, Zhang L, Miao Y, He W, Shi W, Li Y, Ji B, Zhang K, Jiang Z, Kaluri R. DAFLNet: Dual Asymmetric Feature Learning Network for COVID-19 Disease Diagnosis in X-Rays. Computational and Mathematical Methods in Medicine 2022;2022:1 View
  41. Meraihi Y, Gabis A, Mirjalili S, Ramdane-Cherif A, Alsaadi F. Machine Learning-Based Research for COVID-19 Detection, Diagnosis, and Prediction: A Survey. SN Computer Science 2022;3(4) View
  42. Nazir S, Dickson D, Akram M. Survey of explainable artificial intelligence techniques for biomedical imaging with deep neural networks. Computers in Biology and Medicine 2023;156:106668 View
  43. Hatamleh W, Tarazi H, Subbalakshmi C, Tiwari B, Hashmi M. Analysis of Chest X-Ray Images for the Recognition of COVID-19 Symptoms Using CNN. Wireless Communications and Mobile Computing 2022;2022:1 View
  44. Senan E, Alzahrani A, Alzahrani M, Alsharif N, Aldhyani T, Hemanth J. Automated Diagnosis of Chest X-Ray for Early Detection of COVID-19 Disease. Computational and Mathematical Methods in Medicine 2021;2021:1 View
  45. Demko I, Korchagin E, Cherkashin O, Gordeeva N, Anikin D, Anikina D. Possibilities of information systems for prediction of outcomes of new coronavirus infection COVID-19. Meditsinskiy sovet = Medical Council 2022;(4):42 View
  46. Rezayi S, Ghazisaeedi M, Kalhori S, Saeedi S. Artificial Intelligence Approaches on X-ray-oriented Images Process for Early Detection of COVID-19. Journal of Medical Signals & Sensors 2022;12(3):233 View
  47. Roy P, Kumar A. Early prediction of COVID-19 using ensemble of transfer learning. Computers and Electrical Engineering 2022;101:108018 View
  48. Xu F, Lou K, Chen C, Chen Q, Wang D, Wu J, Zhu W, Tan W, Zhou Y, Liu Y, Wang B, Zhang X, Zhang Z, Zhang J, Sun M, Zhang G, Dai G, Hu H. An original deep learning model using limited data for COVID‐19 discrimination: A multicenter study. Medical Physics 2022;49(6):3874 View
  49. Hertel R, Benlamri R. Deep Learning Techniques for COVID-19 Diagnosis and Prognosis Based on Radiological Imaging. ACM Computing Surveys 2023;55(12):1 View
  50. Hassan H, Ren Z, Zhou C, Khan M, Pan Y, Zhao J, Huang B. Supervised and weakly supervised deep learning models for COVID-19 CT diagnosis: A systematic review. Computer Methods and Programs in Biomedicine 2022;218:106731 View
  51. Özbilge E, Sanlidag T, Ozbilge E, Baddal B. Artificial Intelligence-Assisted RT-PCR Detection Model for Rapid and Reliable Diagnosis of COVID-19. Applied Sciences 2022;12(19):9908 View
  52. Murillo-González A, González D, Jaramillo L, Galeano C, Tavera F, Mejía M, Hernández A, Rivera D, Paniagua J, Ariza-Jiménez L, Garcés Echeverri J, Diaz León C, Serna-Higuita D, Barrios W, Arrázola W, Mejía M, Arango S, Marín Ramírez D, Salinas-Miranda E, Quintero O. Medical decision support system using weakly-labeled lung CT scans. Frontiers in Medical Technology 2022;4 View
  53. Khan M, Alhaisoni M, Tariq U, Hussain N, Majid A, Damaševičius R, Maskeliūnas R. COVID-19 Case Recognition from Chest CT Images by Deep Learning, Entropy-Controlled Firefly Optimization, and Parallel Feature Fusion. Sensors 2021;21(21):7286 View
  54. Alizadehsani R, Sharifrazi D, Izadi N, Joloudari J, Shoeibi A, Gorriz J, Hussain S, Arco J, Sani Z, Khozeimeh F, Khosravi A, Nahavandi S, Islam S, Acharya U. Uncertainty-Aware Semi-Supervised Method Using Large Unlabeled and Limited Labeled COVID-19 Data. ACM Transactions on Multimedia Computing, Communications, and Applications 2021;17(3s):1 View
  55. Irkham I, Ibrahim A, Nwekwo C, Al-Turjman F, Hartati Y. Current Technologies for Detection of COVID-19: Biosensors, Artificial Intelligence and Internet of Medical Things (IoMT): Review. Sensors 2022;23(1):426 View
  56. Wang R, Ji C, Zhang Y, Li Y. Focus, Fusion, and Rectify: Context-Aware Learning for COVID-19 Lung Infection Segmentation. IEEE Transactions on Neural Networks and Learning Systems 2022;33(1):12 View
  57. van der Velden B, Kuijf H, Gilhuijs K, Viergever M. Explainable artificial intelligence (XAI) in deep learning-based medical image analysis. Medical Image Analysis 2022;79:102470 View
  58. Nagaoka T, Kozuka T, Yamada T, Habe H, Nemoto M, Tada M, Abe K, Handa H, Yoshida H, Ishii K, Kimura Y. A Deep Learning System to Diagnose COVID-19 Pneumonia Using Masked Lung CT Images to Avoid AI-generated COVID-19 Diagnoses that Include Data outside the Lungs. Advanced Biomedical Engineering 2022;11(0):76 View
  59. Negrini D, Danese E, Henry B, Lippi G, Montagnana M. Artificial intelligence at the time of COVID-19: who does the lion’s share?. Clinical Chemistry and Laboratory Medicine (CCLM) 2022;60(12):1881 View
  60. Park S, Ko T, Park C, Kim Y, Choi I. Deep Learning Model Based on 3D Optical Coherence Tomography Images for the Automated Detection of Pathologic Myopia. Diagnostics 2022;12(3):742 View
  61. Wang L, Zhang Y, Wang D, Tong X, Liu T, Zhang S, Huang J, Zhang L, Chen L, Fan H, Clarke M. Artificial Intelligence for COVID-19: A Systematic Review. Frontiers in Medicine 2021;8 View
  62. Min Kim H, Ko T, Young Choi I, Myong J. Asbestosis diagnosis algorithm combining the lung segmentation method and deep learning model in computed tomography image. International Journal of Medical Informatics 2022;158:104667 View
  63. Wang S, Attique Khan M, Govindaraj V, L. Fernandes S, Zhu Z, Zhang Y. Deep Rank-Based Average Pooling Network for Covid-19 Recognition. Computers, Materials & Continua 2022;70(2):2797 View
  64. Sri Kavya N, shilpa T, Veeranjaneyulu N, Divya Priya D. Detecting Covid19 and pneumonia from chest X-ray images using deep convolutional neural networks. Materials Today: Proceedings 2022;64:737 View
  65. Wang S, Fernandes S, Zhu Z, Zhang Y. AVNC: Attention-Based VGG-Style Network for COVID-19 Diagnosis by CBAM. IEEE Sensors Journal 2022;22(18):17431 View
  66. Xu G, Liu C, Liu J, Ding Z, Shi F, Guo M, Zhao W, Li X, Wei Y, Gao Y, Ren C, Shen D. Cross-Site Severity Assessment of COVID-19 From CT Images via Domain Adaptation. IEEE Transactions on Medical Imaging 2022;41(1):88 View
  67. Jalali Moghaddam M, Ghavipour M. Towards smart diagnostic methods for COVID-19: Review of deep learning for medical imaging. IPEM-Translation 2022;3-4:100008 View
  68. Javidi M, Abbaasi S, Naybandi Atashi S, Jampour M. COVID-19 early detection for imbalanced or low number of data using a regularized cost-sensitive CapsNet. Scientific Reports 2021;11(1) View
  69. A-Alam N, Khan M, Nasir M. Using fused Contourlet transform and neural features to spot COVID19 infections in CT scan images. Intelligent Systems with Applications 2023;17:200182 View
  70. Chen J, Li Y, Guo L, Zhou X, Zhu Y, He Q, Han H, Feng Q. Machine learning techniques for CT imaging diagnosis of novel coronavirus pneumonia: a review. Neural Computing and Applications 2024;36(1):181 View
  71. Abugabah A, Mehmood A, Ali AL Zubi A, Sanzogni L. Smart COVID-3D-SCNN: A Novel Method to Classify X-ray Images of COVID-19. Computer Systems Science and Engineering 2022;41(3):997 View
  72. Pintelas E, Pintelas P. A 3D-CAE-CNN model for Deep Representation Learning of 3D images. Engineering Applications of Artificial Intelligence 2022;113:104978 View
  73. Siddiqui S, Arifeen M, Hopgood A, Good A, Gegov A, Hossain E, Rahman W, Hossain S, Al Jannat S, Ferdous R, Masum S. Deep Learning Models for the Diagnosis and Screening of COVID-19: A Systematic Review. SN Computer Science 2022;3(5) View
  74. Ishiwata Y, Miura K, Kishimoto M, Nomura K, Sawamura S, Magami S, Ikawa M, Yamashiro T, Utsunomiya D. Comparison of CO-RADS Scores Based on Visual and Artificial Intelligence Assessments in a Non-Endemic Area. Diagnostics 2022;12(3):738 View
  75. Teodoro A, Silva D, Saadi M, Okey O, Rosa R, Otaibi S, Rodríguez D. An Analysis of Image Features Extracted by CNNs to Design Classification Models for COVID-19 and Non-COVID-19. Journal of Signal Processing Systems 2023;95(2-3):101 View
  76. Al Rahhal M, Bazi Y, Jomaa R, AlShibli A, Alajlan N, Mekhalfi M, Melgani F. COVID-19 Detection in CT/X-ray Imagery Using Vision Transformers. Journal of Personalized Medicine 2022;12(2):310 View
  77. Yaşar H, Ceylan M, Cebeci H, Kılınçer A, Kanat F, Koplay M. A novel study to increase the classification parameters on automatic three-class COVID-19 classification from CT images, including cases from Turkey. Journal of Experimental & Theoretical Artificial Intelligence 2024;36(4):563 View
  78. Ko H, Huh J, Kim K, Chung H, Ko Y, Kim J, Lee J, Lee J. A Deep Residual U-Net Algorithm for Automatic Detection and Quantification of Ascites on Abdominopelvic Computed Tomography Images Acquired in the Emergency Department: Model Development and Validation. Journal of Medical Internet Research 2022;24(1):e34415 View
  79. Ho T, Kim G, Kim T, Choi S, Park E. Classification of rotator cuff tears in ultrasound images using deep learning models. Medical & Biological Engineering & Computing 2022;60(5):1269 View
  80. Shankar K, Perumal E, Díaz V, Tiwari P, Gupta D, Saudagar A, Muhammad K. An optimal cascaded recurrent neural network for intelligent COVID-19 detection using Chest X-ray images. Applied Soft Computing 2021;113:107878 View
  81. Fusco R, Grassi R, Granata V, Setola S, Grassi F, Cozzi D, Pecori B, Izzo F, Petrillo A. Artificial Intelligence and COVID-19 Using Chest CT Scan and Chest X-ray Images: Machine Learning and Deep Learning Approaches for Diagnosis and Treatment. Journal of Personalized Medicine 2021;11(10):993 View
  82. Abiyev R, Ismail A, Ahmadian A. COVID-19 and Pneumonia Diagnosis in X-Ray Images Using Convolutional Neural Networks. Mathematical Problems in Engineering 2021;2021:1 View
  83. Liang H, Guo Y, Chen X, Ang K, He Y, Jiang N, Du Q, Zeng Q, Lu L, Gao Z, Li L, Li Q, Nie F, Ding G, Huang G, Chen A, Li Y, Guan W, Sang L, Xu Y, Chen H, Chen Z, Li S, Zhang N, Chen Y, Huang D, Li R, Li J, Cheng B, Zhao Y, Li C, Xiong S, Wang R, Liu J, Wang W, Huang J, Cui F, Xu T, Lure F, Zhan M, Huang Y, Yang Q, Dai Q, Liang W, He J, Zhong N. Artificial intelligence for stepwise diagnosis and monitoring of COVID-19. European Radiology 2022;32(4):2235 View
  84. Khan A, Khan S, Saif M, Batool A, Sohail A, Waleed Khan M. A Survey of Deep Learning Techniques for the Analysis of COVID-19 and their usability for Detecting Omicron. Journal of Experimental & Theoretical Artificial Intelligence 2024;36(8):1779 View
  85. Ren Q, Zhou B, Tian L, Guo W. Detection of COVID-19 With CT Images Using Hybrid Complex Shearlet Scattering Networks. IEEE Journal of Biomedical and Health Informatics 2022;26(1):194 View
  86. Florescu L, Streba C, Şerbănescu M, Mămuleanu M, Florescu D, Teică R, Nica R, Gheonea I. Federated Learning Approach with Pre-Trained Deep Learning Models for COVID-19 Detection from Unsegmented CT images. Life 2022;12(7):958 View
  87. Fallahpoor M, Chakraborty S, Heshejin M, Chegeni H, Horry M, Pradhan B. Generalizability assessment of COVID-19 3D CT data for deep learning-based disease detection. Computers in Biology and Medicine 2022;145:105464 View
  88. Alhaj T, Idris I, Elhaj F, Elhassan T, Remli M, Siraj M, Mohd Rahim M. Preliminary Stages for COVID-19 Detection Using Image Processing. Diagnostics 2022;12(12):3171 View
  89. Lasker A, Obaidullah S, Chakraborty C, Roy K. Application of Machine Learning and Deep Learning Techniques for COVID-19 Screening Using Radiological Imaging: A Comprehensive Review. SN Computer Science 2022;4(1) View
  90. Sufian M, Moung E, Hijazi M, Yahya F, Dargham J, Farzamnia A, Sia F, Mohd Naim N. COVID-19 Classification through Deep Learning Models with Three-Channel Grayscale CT Images. Big Data and Cognitive Computing 2023;7(1):36 View
  91. Derevitskii I, Mramorov N, Usoltsev S, Kovalchuk S. Hybrid Bayesian Network-Based Modeling: COVID-19-Pneumonia Case. Journal of Personalized Medicine 2022;12(8):1325 View
  92. Shiri I, Arabi H, Salimi Y, Sanaat A, Akhavanallaf A, Hajianfar G, Askari D, Moradi S, Mansouri Z, Pakbin M, Sandoughdaran S, Abdollahi H, Radmard A, Rezaei‐Kalantari K, Ghelich Oghli M, Zaidi H. COLI‐Net: Deep learning‐assisted fully automated COVID‐19 lung and infection pneumonia lesion detection and segmentation from chest computed tomography images. International Journal of Imaging Systems and Technology 2022;32(1):12 View
  93. Mulrenan C, Rhode K, Fischer B. A Literature Review on the Use of Artificial Intelligence for the Diagnosis of COVID-19 on CT and Chest X-ray. Diagnostics 2022;12(4):869 View
  94. Li S, Liu Y, Kumar V. Deep Learning-Based Mental Health Model on Primary and Secondary School Students’ Quality Cultivation. Computational Intelligence and Neuroscience 2022;2022:1 View
  95. Lan T, Cai Z, Ye B. A Novel Spline Algorithm Applied to COVID-19 Computed Tomography Image Reconstruction. IEEE Transactions on Industrial Informatics 2022;18(11):7804 View
  96. Chen D. Analysis of Machine Learning Methods for COVID-19 Detection Using Serum Raman Spectroscopy. Applied Artificial Intelligence 2021;35(14):1147 View
  97. Yang L, Wang S, Zhang Y. EDNC: Ensemble Deep Neural Network for COVID-19 Recognition. Tomography 2022;8(2):869 View
  98. Tzeng I, Hsieh P, Su W, Hsieh T, Chang S. Artificial Intelligence-Assisted Chest X-ray for the Diagnosis of COVID-19: A Systematic Review and Meta-Analysis. Diagnostics 2023;13(4):584 View
  99. Wang Y, Tsai D, Yen L, Yao Y, Chiang T, Chiu C, Lin T, Yeh K, Chang F. Clinical Characteristics of COVID-19 Patients and Application to an Artificial Intelligence System for Disease Surveillance. Journal of Clinical Medicine 2022;11(5):1437 View
  100. Aria M, Nourani E, Golzari Oskouei A, Liu J. ADA-COVID: Adversarial Deep Domain Adaptation-Based Diagnosis of COVID-19 from Lung CT Scans Using Triplet Embeddings. Computational Intelligence and Neuroscience 2022;2022:1 View
  101. Monday H, Li J, Nneji G, Nahar S, Hossin M, Jackson J, Ejiyi C. COVID-19 Diagnosis from Chest X-ray Images Using a Robust Multi-Resolution Analysis Siamese Neural Network with Super-Resolution Convolutional Neural Network. Diagnostics 2022;12(3):741 View
  102. Hasan M, Jawad M, Hasan K, Partha S, Masba M, Saha S, Moni M. COVID-19 identification from volumetric chest CT scans using a progressively resized 3D-CNN incorporating segmentation, augmentation, and class-rebalancing. Informatics in Medicine Unlocked 2021;26:100709 View
  103. Arco J, Ortiz A, Ramírez J, Zhang Y, Górriz J. Tiled Sparse Coding in Eigenspaces for Image Classification. International Journal of Neural Systems 2022;32(03) View
  104. Liu J, Sun W, Zhao X, Zhao J, Jiang Z. Deep feature fusion classification network (DFFCNet): Towards accurate diagnosis of COVID-19 using chest X-rays images. Biomedical Signal Processing and Control 2022;76:103677 View
  105. Costa Y, Silva S, Teixeira L, Pereira R, Bertolini D, Britto A, Oliveira L, Cavalcanti G. COVID-19 Detection on Chest X-ray and CT Scan: A Review of the Top-100 Most Cited Papers. Sensors 2022;22(19):7303 View
  106. Bhosale Y, Patnaik K. Application of Deep Learning Techniques in Diagnosis of Covid-19 (Coronavirus): A Systematic Review. Neural Processing Letters 2023;55(3):3551 View
  107. Li W, Deng X, Zhao H, Shao H, Jiang Y. COVID-19 diagnosis prediction using classical-to-quantum ensemble model with transfer learning for CT scan images. The Imaging Science Journal 2021;69(5-8):319 View
  108. Liao J, Liu L, Duan H, Huang Y, Zhou L, Chen L, Wang C. Using a Convolutional Neural Network and Convolutional Long Short-term Memory to Automatically Detect Aneurysms on 2D Digital Subtraction Angiography Images: Framework Development and Validation. JMIR Medical Informatics 2022;10(3):e28880 View
  109. Akl A, Hosny K, Fouda M, Salah A, Son L. A hybrid CNN and ensemble model for COVID-19 lung infection detection on chest CT scans. PLOS ONE 2023;18(3):e0282608 View
  110. Liu J, Feng Q, Miao Y, He W, Shi W, Jiang Z. COVID-19 disease identification network based on weakly supervised feature selection. Mathematical Biosciences and Engineering 2023;20(5):9327 View
  111. Karbasi Z, Gohari S, Sabahi A. Bibliometric analysis of the use of artificial intelligence in COVID‐19 based on scientific studies. Health Science Reports 2023;6(5) View
  112. Dabbagh R, Jamal A, Bhuiyan Masud J, Titi M, Amer Y, Khayat A, Alhazmi T, Hneiny L, Baothman F, Alkubeyyer M, Khan S, Temsah M. Harnessing Machine Learning in Early COVID-19 Detection and Prognosis: A Comprehensive Systematic Review. Cureus 2023 View
  113. Mano L, Torres A, Morales A, Cruz C, Cardoso F, Alves S, Faria C, Lanzillotti R, Cerceau R, da Costa R, Figueiredo K, Werneck V. Machine Learning Applied to COVID-19: A Review of the Initial Pandemic Period. International Journal of Computational Intelligence Systems 2023;16(1) View
  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
  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
  117. Zhang J, Liu Y, Lei B, Sun D, Wang S, Zhou C, Ding X, Chen Y, Chen F, Wang T, Huang R, Chen K. GIONet: Global information optimized network for multi-center COVID-19 diagnosis via COVID-GAN and domain adversarial strategy. Computers in Biology and Medicine 2023;163:107113 View
  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
  119. Mohammadian Takaloo V, Hashemzadeh M, Ghavidel Neycharan J. DiagCovidPNA: diagnosing and differentiating COVID-19, viral and bacterial pneumonia from chest X-ray images using a hybrid specialized deep learning approach. Soft Computing 2023 View
  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
  128. Saha P, Nadeem S, Comellas A. A survey on artificial intelligence in pulmonary imaging. WIREs Data Mining and Knowledge Discovery 2023;13(6) View
  129. Pandey K. A Deep Learning based Solution (Covi-DeteCT) Amidst COVID-19. Current Medical Imaging Formerly Current Medical Imaging Reviews 2022;19(5):510 View
  130. Pintelas E, Livieris I, Pintelas P. Explainable Feature Extraction and Prediction Framework for 3D Image Recognition Applied to Pneumonia Detection. Electronics 2023;12(12):2663 View
  131. Hou Y, Navarro-Cía M. A computationally-inexpensive strategy in CT image data augmentation for robust deep learning classification in the early stages of an outbreak. Biomedical Physics & Engineering Express 2023;9(5):055003 View
  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
  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;28(5):1936 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 2025;42(1) View
  136. Negreiros R, Silva I, Alves A, Valadares D, Perkusich A, Baptista C. COVID-19 Diagnosis Through Deep Learning Techniques and Chest X-Ray Images. SN Computer Science 2023;4(5) View
  137. Arunachalam A, Ravi V, Acharya V, Pham T. Toward Data-Model-Agnostic Autonomous Machine-Generated Data Labeling and Annotation Platform: COVID-19 Autoannotation Use Case. IEEE Transactions on Engineering Management 2023;70(8):2695 View
  138. Archana K, Kaur A, Gulzar Y, Hamid Y, Mir M, Soomro A. Deep learning models/techniques for COVID-19 detection: a survey. Frontiers in Applied Mathematics and Statistics 2023;9 View
  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
  140. Jalloul M, Alkhulaifat D, Miranda-Schaeubinger M, De Leon Benedetti L, Otero H, Dako F. Artificial Intelligence in Chest Radiology: Advancements and Applications for Improved Global Health Outcomes. Current Pulmonology Reports 2024;13(1):1 View
  141. Shoeibi A, Khodatars M, Jafari M, Ghassemi N, Sadeghi D, Moridian P, Khadem A, Alizadehsani R, Hussain S, Zare A, Sani Z, Khozeimeh F, Nahavandi S, Acharya U, Gorriz J. Automated detection and forecasting of COVID-19 using deep learning techniques: A review. Neurocomputing 2024;577:127317 View
  142. Hijazi M, Abdul Yazid N, Nohuddin P, Abdul Karim S, Syed Zainol Abidin S, Skala V. COVID-19 Detection using Deep Learning Classifiers with Histogram Equalization and Contour-Based X-Ray Images. ITM Web of Conferences 2024;63:01006 View
  143. Miah M, Venkatraman S. Artificial Intelligence for Early Detection and Diagnosis of COVID-19: Immense Potential of a Powerful Technology. Journal of Health Management 2024;26(2):369 View
  144. Xi Y, Zhang N, Li B. Small data-driven semantic segmentation of wear debris in ferrography images. Measurement Science and Technology 2024;35(6):066006 View
  145. Zaeri N. Artificial intelligence and machine learning responses to COVID-19 related inquiries. Journal of Medical Engineering & Technology 2023;47(6):301 View
  146. Singh K, Kaur N, Prabhu A. Combating COVID-19 Crisis using Artificial Intelligence (AI) Based Approach: Systematic Review. Current Topics in Medicinal Chemistry 2024;24(8):737 View
  147. Pravin S, Rohith G, V K, Saranya J, Latha B, Vigneshwar K, Krishna S, Nambirajan H, Sumitra Y. PixNet for early diagnosis of COVID-19 using CT images. Multimedia Tools and Applications 2024;84(10):8179 View
  148. Kule D, Elezaj O, Mehtre U. Socio-economic Challenges in COVID Detection using Transfer Learning-Based Methods. WSEAS TRANSACTIONS ON INFORMATION SCIENCE AND APPLICATIONS 2024;21:216 View
  149. Pradeep K, Vemuri R, N V. A Novel Approach to detect COVID-19 from chest X-ray images using CNN. International Journal of Computer Communication and Informatics 2023;5(1):51 View
  150. Ismetoglu A, Canbay Y. Detection of Covid‐19 disease by using privacy‐aware artificial intelligence system. SECURITY AND PRIVACY 2024;7(6) View
  151. Ahuja V, Nair L. Artificial Intelligence and technology in COVID Era. Journal of Anaesthesiology Clinical Pharmacology 2021;37(1):28 View
  152. Smilianets F, Finogenov O. Review of disease identification methods based on computed tomography imagery. Ukrainian Journal of Information Technology 2024;6(1):95 View
  153. Bhati D, Neha F, Amiruzzaman M. A Survey on Explainable Artificial Intelligence (XAI) Techniques for Visualizing Deep Learning Models in Medical Imaging. Journal of Imaging 2024;10(10):239 View
  154. Nanda M, Amaru K, Rosalinda S, Novianty I, Sholihah W, Mindara G, Faricha A, Park T. Higuchi fractal dimension and deep learning on near-infrared spectroscopy for determination of free fatty acid (FFA) content in oil palm fruit. Journal of Agriculture and Food Research 2024;18:101437 View
  155. Buriboev A, Muhamediyeva D, Primova H, Sultanov D, Tashev K, Jeon H. Concatenated CNN-Based Pneumonia Detection Using a Fuzzy-Enhanced Dataset. Sensors 2024;24(20):6750 View
  156. Raman R, Singhania M, Nedungadi P. Advancing the United Nations Sustainable Development Goals Through Digital Health Research: 25 Years of Contributions From the Journal of Medical Internet Research. Journal of Medical Internet Research 2024;26:e60025 View
  157. Hadj Bouzid A, Berrani S, Yahiaoui S, Belaid A, Belazzougui D, Djouad M, Bensalah K, Belbachir H, Naïli Q, Abdi M, Tliba S. Deep learning-based Covid-19 diagnosis: a thorough assessment with a focus on generalization capabilities. EURASIP Journal on Image and Video Processing 2024;2024(1) View
  158. Salama G, Mohamed A, Abd-Ellah M. Machine learning and deep learning covid-19 diagnosis system: key achievements, lessons learned, and a transfer learning algorithm. Soft Computing 2024 View
  159. Chen C, Mat Isa N, Liu X. A review of convolutional neural network based methods for medical image classification. Computers in Biology and Medicine 2025;185:109507 View
  160. Li Y, Zhao L, Zhang H, Cao W. DBCE-Net: A Novel Deep Learning Framework for Annual Mapping of Coastal Aquaculture Ponds in China with Sentinel-2 Data. Remote Sensing 2025;17(3):362 View
  161. Fouad S, Usman M, Kabir R, Rajasekaran A, Morlese J, Nagori P, Bhatia B. Explained Deep Learning Framework for COVID-19 Detection in Volumetric CT Images Aligned with the British Society of Thoracic Imaging Reporting Guidance: A Pilot Study. Journal of Imaging Informatics in Medicine 2025 View
  162. Haseeb A, Khan M, Alhaisoni M, Aldehim G, Jamel L, Tariq U, Kim T, Cha J. A Fusion of Residual Blocks and Stack Auto Encoder Features for Stomach Cancer Classification. Computers, Materials & Continua 2023;77(3):3895 View
  163. Enkvetchakul P, Khonjun S, Pitakaso R, Srichok T, Luesak P, Kaewta C, Gonwirat S, Boonmee C, Noowattana M, Srisuwandee T. Advanced AI techniques for root disease classification in dental X-rays using deep learning and metaheuristic approach. Intelligent Systems with Applications 2025;26:200526 View
  164. Wang M, He Y, Peng L, Song X, Dong S, Gong Y. Cross-Domain Invariant Feature Absorption and Domain-Specific Feature Retention for Domain Incremental Chest X-Ray Classification. IEEE Transactions on Medical Imaging 2025;44(5):2041 View

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

Conference Proceedings

  1. Serte S, Serener A. 2020 4th International Symposium on Multidisciplinary Studies and Innovative Technologies (ISMSIT). Discerning COVID-19 from mycoplasma and viral pneumonia on CT images via deep learning View
  2. Mohan N, Kabeer S, Nasir N. 2021 28th IEEE International Conference on Electronics, Circuits, and Systems (ICECS). Artificial Intelligence (AI) in the diagnosis of COVID-19 Detection: A Review View
  3. Asif S, Wenhui Y, Jinhai S, Waheed Z, Yueyang Y, Jin H. 2022 IEEE International Conference on Bioinformatics and Biomedicine (BIBM). CVD19-Net: An Automated Deep Learning Model for COVID-19 Screening using Chest CT Images View
  4. Zahrani N, Hedjar R. 2022 13th International Conference on Information and Communication Systems (ICICS). Comparison Study Of Deep-Learning Architectures For Classification of Thoracic Pathology View
  5. Mittal B, Oh J, Jiang X, Fujita H. Thirteenth International Conference on Digital Image Processing (ICDIP 2021). CoviNet: Covid-19 diagnosis using machine learning analyses for computerized tomography images View
  6. Rithesh K, Wong L, See J, Chan W, Ng K. 2022 IEEE International Conference on Consumer Electronics - Taiwan. DECOVID-CT: Lightweight 3D CNN for COVID-19 Infection Prediction View
  7. Saad Y, Mustapha A, Cherry A. 2021 Sixth International Conference on Advances in Biomedical Engineering (ICABME). Automatic classification between COVID-19 pneumonia, lung cancer and normal lung tissues on chest CT Scans View
  8. Li Z. 2022 3rd International Conference on Computer Vision, Image and Deep Learning & International Conference on Computer Engineering and Applications (CVIDL & ICCEA). COVID-19 Classification with CT Scan and Advanced Deep Learning Technologies View
  9. Liang S, Zhang W, Gu Y. 2021 IEEE/CVF International Conference on Computer Vision Workshops (ICCVW). A hybrid and fast deep learning framework for Covid-19 detection via 3D Chest CT Images View
  10. Zhang Y, Rong L, Li X, Tiwari P, Zheng Q, Liang H. 2021 IEEE International Conference on Bioinformatics and Biomedicine (BIBM). MedSeq2Seq: A Medical Knowledge Enriched Sequence to Sequence Learning Model for COVID-19 Diagnosis View
  11. William F, Serener A, Serte S. 2022 International Congress on Human-Computer Interaction, Optimization and Robotic Applications (HORA). Patient gender identity information in Covid-19 severity detection on 3D chest CT scans via deep learning View
  12. Altaf F, Islam S, Akhtar N. 2021 Digital Image Computing: Techniques and Applications (DICTA). Resetting the baseline: CT-based COVID-19 diagnosis with Deep Transfer Learning is not as accurate as widely thought View
  13. Karimzadeh R, Rajabi N, Fatemizadeh E, Arabi H. 2021 28th National and 6th International Iranian Conference on Biomedical Engineering (ICBME). 3D dilated and residual convolutional neural network for COVID-19 detection from the chest computed tomography View
  14. Agrawal S, Singh A, Tiwari A, Mishra A, Tripathi A. Proceedings of the 2022 Fourteenth International Conference on Contemporary Computing. A Systematic Survey on COVID 19 Detection and Diagnosis by Utilizing Deep Learning Techniques and Modalities of Radiology View
  15. Riyadi S, Septiari T, Damarjati C, Ramli S. 2022 IEEE 12th International Conference on Control System, Computing and Engineering (ICCSCE). Covid-19 Detection Based-On CT-Scan Images Using Inception Deep Learning View
  16. Abubakar H, Al-Turjman F, Ameen Z, Mubarak A. 2022 International Conference on Artificial Intelligence of Things and Crowdsensing (AIoTCs). A Review of Deep Learning and Machine Learning Approaches in COVID-19 Detection View
  17. Jebaseeli T, David D, Suriya S. 2023 International Conference on Computer Communication and Informatics (ICCCI). Classification of Influenza from Chest Radiography using Deep Neural Architecture View
  18. Zhang J, Liu Y, Lei B, Sun D, Huang R, Wang T, Chen S, Chen K. 2023 45th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC). Graph Convolution and Self-attention Enhanced CNN with Domain Adaptation for Multi-site COVID-19 Diagnosis View
  19. Cole J, van de Ven C, Matt Sharkey C, Williamson P, Doherty P, Robb F. Extended Abstracts of the 2021 CHI Conference on Human Factors in Computing Systems. r/Coronavirus and the Viral Pandemic View
  20. Kaushik V. 2023 2nd International Conference on Futuristic Technologies (INCOFT). A Transfer Learning-Based Framework Aware of Uncertainty for Diagnosing COVID-19 View
  21. Agrawal S, Sharma D. 2023 12th International Conference on System Modeling & Advancement in Research Trends (SMART). Unveiling AI Insights: Navigating COVID-19 with Machine Learning and Deep Learning View
  22. Liang Z, Lu H, You C, Zhu W, Xie L, Yao Y. 2023 13th International Conference on Information Technology in Medicine and Education (ITME). PDCapsNet: A Convolution Neural Network Method for COVID-19 Detection from Chest X-Ray Images View

Dissertations

  1. . COVID-19 Diagnosis and Segmentation Using Machine Learning Analyses of Lung Computerized Tomography. View