Abstract
Pneumonia is also known as Bronchopneumonia is a condition of the lungs which primarily affects the air sacks called alveoli. It results in dry and productive cough, fever, weakness, chest pain, and difficulties in breathing. Pneumonia is caused by infections brought upon by microorganisms such as bacteria and viruses. The diagnosis of pneumonia is compassed by scrutinizing X-ray images of the chest. This diagnosis is subjective to factors such as the unclear appearance of the disease in the X-ray image. Hence, artificial intelligence-based systems are required to beacon the clinics. In this study, we have implemented a very popular convolutional neural network model known as VGG16 for the diagnosis of pneumonia. In the training stage, we have used transfer learning and fine-tuning. We were able to achieve an accuracy of 90.54% with a 98.71% recall and 87.69% precision using the aforementioned convolutional neural network model.
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Thakur, S., Goplani, Y., Arora, S., Upadhyay, R., Sharma, G. (2021). Chest X-Ray Images Based Automated Detection of Pneumonia Using Transfer Learning and CNN. In: Bansal, P., Tushir, M., Balas, V., Srivastava, R. (eds) Proceedings of International Conference on Artificial Intelligence and Applications. Advances in Intelligent Systems and Computing, vol 1164. Springer, Singapore. https://doi.org/10.1007/978-981-15-4992-2_31
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DOI: https://doi.org/10.1007/978-981-15-4992-2_31
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