Abstract: Pneumonia Detection through X-Ray Using Deep Learning is a web application which is used to detect the presence of Pneumonia from a collection of chest X-ray samples. Remarkable classification performance is achieved using methods that rely solely on transfer learning approaches or traditional handcrafted techniques. We constructed a convolutional neural network (CNN) model that extract features from a given chest X-ray image then it classifies it to determine if a person is infected with pneumonia. Reliability and interpretability challenges can be mitigated by this model that are often faced when dealing with medical imagery.
Key Word: Pneumonia, Detection, X-ray, Convolutional Neural Network (CNN), infected, Deep Learning and medical
[1] M. Fiszman, W. W. Chapman, S. R. Evans, and P. J. Haug, ―Automatic identification of pneumonia related concepts on chest x-ray reports.,‖ in Proc. of the AMIA Symposium, p. 67, American Medical Informatics Association, 1999.
[2] W. W. Chapman, M. Fizman, B. E. Chapman, and P. J. Haug, ―A comparison of classification algorithms to automatically identify chest xray reports that support pneumonia,‖ Journal of Biomedical Informatics, vol. 34, no. 1, pp. 4–14, 2001.
[3] E. A. Mendonca, J. Haas, L. Shagina, E. Larson, and C. Friedman, ―Extracting information on pneumonia in infants using natural language processing of radiology reports,‖ Journal of Biomedical Iinformatics, vol. 38, no. 4, pp. 314–321, 2005.
[4] P. Rajpurkar, J. Irvin, K. Zhu, B. Yang, H. Mehta, T. Duan, D. Ding, A. Bagul, C. Langlotz, K. Shpanskaya, et al., ―Chexnet: Radiologistlevel pneumonia detection on chest x-rays with deep learning,‖ ArXiv preprint arXiv:1711.05225, 2017.
[5] N. Parveen and M. M. Sathik, ―Detection of pneumonia in chest Xray images,‖ Journal of X-ray Science and Technology, vol. 19, no. 4, pp. 423–428, 2011.