Development of Pneumonia Disease Detection Model Based on Deep Learning Algorithm

Pneumonia represents a life-endangering and deadly disease that results from viral or bacterial infection in the human lungs. The earlier pneumonia’s diagnosing is an essential aspect processes of successful treatment. Recently, developed methods deep learning include several layers processing to comprehend stratified data representation have obtained best various domains, especially identification classification diseases. Therefore, for improving systems’ performance detecting pneumonia disease, there requirement implementing automatic models based on ability diagnose images chest X-rays facilitate detection process novices experts. A convolutional neural network (CNN) model this paper via utilizing X-rays. proposed framework encompasses two main stages: stage image preprocessing extracting features classification. CNN provides high precision, recall, F1-score, accuracy by 98%, 97%, 99.82%, respectively. Regarding results, model-based has achieved better result consistency accuracy, it outperformed other pretrained such as residual networks (ResNet 50) VGG16. Furthermore, exceeds recently existing presented literature. Thus, significant all measures can provide effective services patient care decrease rates mortality.