Publication Type : Journal Article
Publisher : IEEE
Source : 2024 15th International Conference on Computing Communication and Networking Technologies (ICCCNT)
Url : https://ieeexplore.ieee.org/abstract/document/10725326
Campus : Bengaluru
School : School of Computing
Year : 2024
Abstract : Pneumonia is a prominent cause of illness and death worldwide. The early and precise diagnosis of the disease remains essential for effective treatment of the patient. Traditional methods of diagnosis, while effective, often involve significant time and expertise, that can pose numerous challenges and difficulties during situations with limited resources and in peak demand times. Many recent advances in deep learning and artificial intelligence have shown positive findings in the processing of medical pictures. Chest radiographs have been extensively studied for different purposes, especially in the diagnosis of diseases like Pneumonia, Tuberculosis, Asthma, Bronchitis, Pneumothorax, and many more. This paper focuses on using many Deep Learning architectures and Artificial intelligence concepts, such as explainable AI, to use patients’ chest X-rays to detect pneumonia in patients in its early phase.
Cite this Research Publication : Bhanusri, Kodati, Koti Leela Sai Praneeth Reddy, Kandukuri Jashwanth, Tripty Singh, Amrita Tripathi, and Payel Patra. "Transformative Insights into Pneumonia Detection with a Novel Artificial Intelligence and Deep Learning Approach." In 2024 15th International Conference on Computing Communication and Networking Technologies (ICCCNT), pp. 1-7. IEEE, 2024.