Deep Learning-Based Pneumonia Detection Using CNN and ANN  Pretrained VGG16 Model

Author(s)	Mr. Seepana Satish, Dr. S BALAMURALI
Country	India
Abstract	The recent significant growth in the volume of available data has led to the widespread adoption of artificial intelligence across various disciplines. The use of artificial intelligence and machine learning in medicine is increasing, particularly in fields that utilize numerous types of biological images and where diagnostic processes rely on collecting and analysing large numbers of digital images. Machine learning enhances the accuracy and consistency of medical image interpretation. To improve decision-making in establishing accurate diagnoses, this research explores the application of machine learning algorithms to interpret chest X-ray images. The paper focuses on employing a deep learning approach based on a convolutional neural network to develop a processing model. This model aims to assist in a classification task that determines whether a chest X-ray shows changes associated with pneumonia, categorizing the images into two groups based on the detection results.
Keywords	Pneumonia Detection, Deep Learning, CNN, VGG16, Transfer Learning, Medical Imaging
Field	Engineering
Published In	Volume 16, Issue 3, July-September 2025
Published On	2025-08-24
DOI	https://doi.org/10.71097/IJSAT.v16.i3.7834
Short DOI	https://doi.org/g9x3zk

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