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Detection of Pneumonia in Chest X-Ray Using Ensemble Learners and Transfer Learning with Deep Learning Models

Publication Type : Conference Paper

Publisher : IEEE

Source : 2023 14th International Conference on Computing Communication and Networking Technologies (ICCCNT)

Url : https://doi.org/10.1109/ICCCNT56998.2023.10307035

Campus : Bengaluru

School : School of Computing

Year : 2024

Abstract : A commonly implemented imaging method used for detecting/diagnosing pneumonia is chest X-ray images, but interpreting these images can be extremely complicated requiring advanced skill sets. In this document, we introduce an innovative approach using ensemble learning which combines several pre-trained Deep Learning models' strengths with advanced transfer learning techniques aimed at enhancing lung infection detection through deep-learning predictive capacity utilization. We evaluated our methodology using publicly available datasets containing numerous X-ray scans resulting in optimally accurate predictions that could have substantial implications concerning medical practice improvement efficiency-wise when diagnosing patients exhibiting symptoms matching those indicative of pneumonic infections, thus allowing us to proceed forward successfully implementing more streamlined protocols going onward into future clinical settings.

Cite this Research Publication : H. Bysani, S. Garg, A. Danda, T. Singh, J. C and P. Duraisamy, "Detection of Pneumonia in Chest X-Ray Using Ensemble Learners and Transfer Learning with Deep Learning Models," 2023 14th International Conference on Computing Communication and Networking Technologies (ICCCNT), Delhi, India, 2023

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