ABSTRACT
The research paper discuss the Artificial Intelligence based Multiple Transfer Learning Mechanism in identification of lung diseases like pneumothorax, tension pneumothorax from a set of chest X-rays. Pneumothorax being a primary stage of many sorts of pulmonary diseases, it has now a days being noticed as an impact with COVID cases due to the insertion of the tubes into the lungs. The proper diagnosis of the various stages of Pneumothorax is thus essential in the current scenario. Identification of the patients with Pneumothrax with less diagnostic time is the highlight of this research work. The deep learning technology of AI has enlightened the research in the medical imaging field. The chest X-ray images are with the pre-processing analysis, normalised the images for a uniform image data processing. The advanced method of transfer learning is equipped with modifications in the various fully connected convolutional network layers. The modified transfer learning has been used with DenseNet and VGG 19. The convolutional neural networks with DenseNet201 and VGG19 utilized stochastic gradient decent optimization for parameter optimization. The data set with pneumothorax and tension pneumothorax along with the control set has been trained and validated. The training and validation of these network has proven results with 89% accuracy with VGG19 and 100% accuracy with Densenet. The evaluation of modified Multi-transfer learning algorithm is identified successfully with new random input chest X-ray with a less diagnostic time. © 2022 IEEE.