Publication

Abstract : Pneumonia, a widespread respiratory infection, poses significant health risks and requires timely detection for effective treatment. This study employs transfer learning for pattern identification and predictive modeling for classification in pneumonia detection using chest radiographs. Pre-trained deep learning models are utilized to extract informative features, which are then classified using various machine learning algorithms. A comprehensive evaluation is conducted on a benchmark dataset to assess the performance of the approach. The results demonstrate the effectiveness of transfer learning-based feature extraction combined with machine learning classification in accurate pneumonia detection. The findings contribute to improving diagnostic accuracy and have the potential to enhance healthcare decision-making processes.