Implementation of a Mobile Application based on the Convolutional Neural Network for the Diagnosis of Pneumonia

Pneumonia is the main cause of infant mortality in Peru, which has led to plansfig, such as vaccination campaigns, greater economic investment in health, and the strengthening of specialized medical personnel, however, mortality rates remain high. In this sense, the implementation of new computer technologies such as Deep Learning through the use of the artificial neural network is proposed. The objective of this project was to determine the influence of a mobile application based on a Convolutional Neural Network for the diagnosis of Pneumonia, the project consists of the analysis of images of Chest X-rays with Pneumonia and Normal by means of an application developed called “Diagnost”. The study was carried out considering a control group and a study group formed by 33 medical staff members who used the application. The analysis of the data obtained was made based on the study of 3 indicators, detection time, result in accuracy, and reduction of medical assistance. According to the results, it was concluded that the mobile application based on the convolutional neural network allows the early detection of Pneumonia and allows the reduction of medical assistance, however, it is still necessary to continue working on the accuracy of the diagnosis.

@article{Flores-Rodriguez2022,
  title     = {Implementation of a Mobile Application based on the Convolutional Neural Network for the Diagnosis of Pneumonia},
  journal   = {International Journal of Advanced Computer Science and Applications},
  volume    = {13},
  number    = {8},
  year      = {2022},
  publisher = {The Science and Information Organization},
  author    = {Jazmin Flores-Rodriguez and Michael Cabanillas-Carbonell},
  doi       = {10.14569/IJACSA.2022.0130853},
  url       = {https://doi.org/10.14569/IJACSA.2022.0130853}
}