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

JMIR Theme Issue: COVID-19 Special Issue (2457) Artificial Intelligence (1407) Theme Issue: Novel Coronavirus (COVID-19) Outbreak Rapid Reports (1519) Imaging Informatics (198) Outbreak and Pandemic Preparedness and Management (1737) Clinical Information and Decision Making (1423) Infectious Diseases (non-STD/STI) (1584) Machine Learning (1488)

Published on in Vol 23, No 2 (2021): February

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/23693, first published .
Fast and Accurate Detection of COVID-19 Along With 14 Other Chest Pathologies Using a Multi-Level Classification: Algorithm Development and Validation Study

Fast and Accurate Detection of COVID-19 Along With 14 Other Chest Pathologies Using a Multi-Level Classification: Algorithm Development and Validation Study

Fast and Accurate Detection of COVID-19 Along With 14 Other Chest Pathologies Using a Multi-Level Classification: Algorithm Development and Validation Study

Authors of this article:

Saleh Albahli1, 2 Author Orcid Image ;   Ghulam Nabi Ahmad Hassan Yar3 Author Orcid Image
Article Authors Cited by (26) Tweetations (6) Metrics

Journals

  1. Albahli S, Ayub N, Shiraz M. Coronavirus disease (COVID-19) detection using X-ray images and enhanced DenseNet. Applied Soft Computing 2021;110:107645 View
  2. Moses D. Deep learning applied to automatic disease detection using chest X‐rays. Journal of Medical Imaging and Radiation Oncology 2021;65(5):498 View
  3. Albahli S, Nazir T. AI-CenterNet CXR: An artificial intelligence (AI) enabled system for localization and classification of chest X-ray disease. Frontiers in Medicine 2022;9 View
  4. Sanghvi H, Patel R, Agarwal A, Gupta S, Sawhney V, Pandya A. A deep learning approach for classification of COVID and pneumonia using DenseNet‐201. International Journal of Imaging Systems and Technology 2023;33(1):18 View
  5. Suganyadevi S, Seethalakshmi V. CVD-HNet: Classifying Pneumonia and COVID-19 in Chest X-ray Images Using Deep Network. Wireless Personal Communications 2022;126(4):3279 View
  6. Alathari M, Al Mashhadany Y, Mokhtar M, Burham N, Bin Zan M, A Bakar A, Arsad N. Human Body Performance with COVID-19 Affectation According to Virus Specification Based on Biosensor Techniques. Sensors 2021;21(24):8362 View
  7. Albahli S, Hassan F, Javed A, Irtaza A. Pandemic Analysis and Prediction of COVID-19 Using Gaussian Doubling Times. Computers, Materials & Continua 2022;72(1):833 View
  8. 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
  9. Li D, Zheng C, Zhao J, Liu Y. Diagnosis of heart failure from imbalance datasets using multi-level classification. Biomedical Signal Processing and Control 2023;81:104538 View
  10. AbdElhamid A, AbdElhalim E, Mohamed M, Khalifa F. Multi-Classification of Chest X-rays for COVID-19 Diagnosis Using Deep Learning Algorithms. Applied Sciences 2022;12(4):2080 View
  11. Basha S, Anter A, Hassanien A, Abdalla A. RETRACTED ARTICLE: Hybrid intelligent model for classifying chest X-ray images of COVID-19 patients using genetic algorithm and neutrosophic logic. Soft Computing 2023;27(6):3427 View
  12. Ahmad H, Milne M, Buchlak Q, Ektas N, Sanderson G, Chamtie H, Karunasena S, Chiang J, Holt X, Tang C, Seah J, Bottrell G, Esmaili N, Brotchie P, Jones C. Machine Learning Augmented Interpretation of Chest X-rays: A Systematic Review. Diagnostics 2023;13(4):743 View
  13. Nawaz M, Nazir T, Baili J, Khan M, Kim Y, Cha J. CXray-EffDet: Chest Disease Detection and Classification from X-ray Images Using the EfficientDet Model. Diagnostics 2023;13(2):248 View
  14. Murugappan M, Bourisly A, Prakash N, Sumithra M, Acharya U. Automated semantic lung segmentation in chest CT images using deep neural network. Neural Computing and Applications 2023;35(21):15343 View
  15. Tripathi S, Sharma N. AUTOMATIC DETECTION OF COVID-19 AND VIRAL PNEUMONIA IN X-RAY IMAGES USING DEEP LEARNING APPROACH. Biomedical Engineering: Applications, Basis and Communications 2023;35(02) View
  16. Chen C, Wu C, Chen C, Chung C, Chen S, Lee M, Cheng C, Liao C. Predicting the Risk of Total Hip Replacement by Using A Deep Learning Algorithm on Plain Pelvic Radiographs: Diagnostic Study. JMIR Formative Research 2023;7:e42788 View
  17. Shiri I, Salimi Y, Saberi A, Pakbin M, Hajianfar G, Avval A, Sanaat A, Akhavanallaf A, Mostafaei S, Mansouri Z, Askari D, Ghasemian M, Sharifipour E, Sandoughdaran S, Sohrabi A, Sadati E, Livani S, Iranpour P, Kolahi S, Khosravi B, Khateri M, Bijari S, Atashzar M, Shayesteh S, Babaei M, Jenabi E, Hasanian M, Shahhamzeh A, Ghomi S, Mozafari A, Shirzad‐Aski H, Movaseghi F, Bozorgmehr R, Goharpey N, Abdollahi H, Geramifar P, Radmard A, Arabi H, Rezaei‐Kalantari K, Oveisi M, Rahmim A, Zaidi H. Differentiation of COVID‐19 pneumonia from other lung diseases using CT radiomic features and machine learning: A large multicentric cohort study. International Journal of Imaging Systems and Technology 2024;34(2) View
  18. Nurjahan , Mahbub-Or-Rashid M, Satu M, Tammim S, Sunny F, Moni M. Machine learning and deep learning algorithms in detecting COVID-19 utilizing medical images: a comprehensive review. Iran Journal of Computer Science 2024;7(3):699 View
  19. Ding H, Fan L, Zhang J, Gao G. Deep Learning-Based System Combining Chest X-Ray and Computerized Tomography Images for COVID-19 Diagnosis. British Journal of Hospital Medicine 2024;85(8):1 View
  20. Choudhry I, Iqbal S, Alhussein M, Qureshi A, Aurangzeb K, Naqvi R. Transforming Lung Disease Diagnosis With Transfer Learning Using Chest X‐Ray Images on Cloud Computing. Expert Systems 2024 View
  21. Ibrahim H, Rokbani N, Wali A, Ouahada K, Chabchoub H, Alimi A. A Medical Image Classification Model based on Quantum-Inspired Genetic Algorithm. Engineering, Technology & Applied Science Research 2024;14(5):16692 View
  22. Srikanth P, Behera C, Routhu S. CovidSafe: A Deep Learning Framework for Covid Detection Using Multi-modal Approach. New Generation Computing 2025;43(1) View

Books/Policy Documents

  1. Arteaga-Arteaga H, delaPava M, Mora-Rubio A, Bravo-Ortíz M, Alzate-Grisales J, Arias-Garzón D, López-Murillo L, Buitrago-Carmona F, Villa-Pulgarín J, Mercado-Ruiz E, Martínez Rodríguez F, Palancares Sosa M, Contreras-Ortiz S, Orozco-Arias S, Hassaballah M, de la Iglesia Vayá M, Cardona-Morales O, Tabares-Soto R. AI Applications for Disease Diagnosis and Treatment. View