Chest Disease Detection Using Deep Learning Models

• Author(s): R. Prasanth Reddy; Nagavelli Yogender Nath; Gattu Ramya; Syed Abdul Haq
• Paper ID: 1712444
• Page: 728-736
• Published Date: 31-01-2024
• Published In: Iconic Research And Engineering Journals
• Publisher: IRE Journals
• e-ISSN: 2456-8880
• Volume/Issue: Volume 7 Issue 7 January-2024

Abstract

DL models automate the analysis of medical images through techniques like prediction, segmentation, and classification, often achieving accuracy levels that surpass human capabilities. This is particularly valuable in medical fields where early and accurate diagnosis can significantly affect treatment success rates. For instance, in breast cancer screening, DL models can identify subtle signs of cancer in mammograms more accurately and earlier than traditional methods. Similarly, in lung cancer and brain tumors, DL models facilitate the detection of minute lesions and abnormalities that might be overlooked in manual examinations. This research work focuses on the detection of several chest diseases including lymphoma disease. We have employed DTL and FL models to make the prediction procedure more accessible and faster such as VGG-19. The research's proposed system was developed to predict 14 different kinds of chest conditions, and a comparison between federated learning and deep learning models was made. The proposed study describes a system that can predict lymphoma cancer with reasonable accuracy using sample images taken by various pathologists at different locations. A dataset titled malignant lymphoma classification dataset, which contains more than five thousand images, was used to analyze this study. When the models were evaluated, it was discovered that the VGG-16 model that was suggested had the best accuracy. Consequently, the classification report states that the VGG-16 model is the most effective deep and federated transfer-learning model for lymphoma cancer classification.

Keywords

Chest Diseases, Deep Learning, X-ray, lymphoma, VGG-19, DL models

Citations

IRE Journals:
R. Prasanth Reddy, Nagavelli Yogender Nath, Gattu Ramya, Syed Abdul Haq "Chest Disease Detection Using Deep Learning Models" Iconic Research And Engineering Journals Volume 7 Issue 7 2024 Page 728-736 https://doi.org/10.64388/IREV7I7-1712444

IEEE:
R. Prasanth Reddy, Nagavelli Yogender Nath, Gattu Ramya, Syed Abdul Haq "Chest Disease Detection Using Deep Learning Models" Iconic Research And Engineering Journals, 7(7) https://doi.org/10.64388/IREV7I7-1712444