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

Decision Support for Health Professionals (1185) Imaging Informatics (193) Infectious Diseases (non-STD/STI) (1575)

Published on in Vol 8, No 12 (2020): December

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/21790, first published .
Comprehensive Computer-Aided Decision Support Framework to Diagnose Tuberculosis From Chest X-Ray Images: Data Mining Study

Comprehensive Computer-Aided Decision Support Framework to Diagnose Tuberculosis From Chest X-Ray Images: Data Mining Study

Comprehensive Computer-Aided Decision Support Framework to Diagnose Tuberculosis From Chest X-Ray Images: Data Mining Study

Authors of this article:

Muhammad Owais1 Author Orcid Image ;   Muhammad Arsalan1 Author Orcid Image ;   Tahir Mahmood1 Author Orcid Image ;   Yu Hwan Kim1 Author Orcid Image ;   Kang Ryoung Park1 Author Orcid Image
Article Authors Cited by (15) Tweetations (1) Metrics

Journals

  1. Çallı E, Sogancioglu E, van Ginneken B, van Leeuwen K, Murphy K. Deep learning for chest X-ray analysis: A survey. Medical Image Analysis 2021;72:102125 View
  2. Oloko-Oba M, Viriri S. A Systematic Review of Deep Learning Techniques for Tuberculosis Detection From Chest Radiograph. Frontiers in Medicine 2022;9 View
  3. Guan A, Liu L, Fu X, Liu L. Precision medical image hash retrieval by interpretability and feature fusion. Computer Methods and Programs in Biomedicine 2022;222:106945 View
  4. Aasem M, Iqbal M, Ahmad I, Alassafi M, Alhomoud A. A Survey on Tools and Techniques for Localizing Abnormalities in X-ray Images Using Deep Learning. Mathematics 2022;10(24):4765 View
  5. Haider A, Arsalan M, Nam S, Sultan H, Park K. Computer-aided fish assessment in an underwater marine environment using parallel and progressive spatial information fusion. Journal of King Saud University - Computer and Information Sciences 2023;35(3):211 View
  6. Sultan H, Owais M, Choi J, Mahmood T, Haider A, Ullah N, Park K. Artificial Intelligence-Based Solution in Personalized Computer-Aided Arthroscopy of Shoulder Prostheses. Journal of Personalized Medicine 2022;12(1):109 View
  7. Haider A, Arsalan M, Lee Y, Park K. Deep Features Aggregation-Based Joint Segmentation of Cytoplasm and Nuclei in White Blood Cells. IEEE Journal of Biomedical and Health Informatics 2022;26(8):3685 View
  8. Santosh K, Allu S, Rajaraman S, Antani S. Advances in Deep Learning for Tuberculosis Screening using Chest X-rays: The Last 5 Years Review. Journal of Medical Systems 2022;46(11) View
  9. Khan T, Naqvi S, Meijering E. Leveraging image complexity in macro-level neural network design for medical image segmentation. Scientific Reports 2022;12(1) View
  10. Mahmood T, Choi J, Park K. Artificial intelligence-based classification of pollen grains using attention-guided pollen features aggregation network. Journal of King Saud University - Computer and Information Sciences 2023;35(2):740 View
  11. Akhter Y, Singh R, Vatsa M. AI-based radiodiagnosis using chest X-rays: A review. Frontiers in Big Data 2023;6 View
  12. Hansun S, Argha A, Liaw S, Celler B, Marks G. Machine and Deep Learning for Tuberculosis Detection on Chest X-Rays: Systematic Literature Review. Journal of Medical Internet Research 2023;25:e43154 View
  13. Liu J, Xie H, Lu M, Li Y, Wang B, Sun Z, He W, Wen L, Hou D. CT Image Detection of Pulmonary Tuberculosis Based on the Improved Strategy YOLOv5. International Journal of Swarm Intelligence Research 2023;14(1):1 View
  14. Natarajan S, Sampath P, Arunachalam R, Shanmuganathan V, Dhiman G, Chakrabarti P, Chakrabarti T, Margala M. Early diagnosis and meta-agnostic model visualization of tuberculosis based on radiography images. Scientific Reports 2023;13(1) View