Classification of Pneumonia Disease Through Deep Learning Procedures and Fine-tuning on ResNet50V2 CNN Model Utilizing Chest Xray Images

• Published in: 2023 Global Conference on Information Technologies and Communications (GCITC) pp. 1 - 5
• Main Authors: Gill, Kanwarpartap Singh, Anand, Vatsala, Gupta, Rupesh
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01.12.2023
• Subjects: Classification; CNN; Confusion matrix; Deep learning; Medical treatment; Microorganisms; Model Training; Pathogens; Pneumonia Disease; Pulmonary diseases; ResNet50V2 Model; Vaccines; X-ray imaging
• ISBN: 9798350308143
• DOI: 10.1109/GCITC60406.2023.10426406

Many different types of germs like bacteria, viruses, fungus, and other tiny organisms can make you get pneumonia. Depending on the etiological agent and the patient's health, the intensity of this disease's symptoms might vary from minor to severe. Streptococcus pneumoniae frequently causes viral pneumonia, while influenza viruses and other viruses can cause bacterial pneumonia. Improved pneumonia diagnostic techniques, therapies, and vaccinations are still being researched. In order to increase accuracy, categorization of the pneumonia sickness is done in this study utilising the ResNet50V2 Model and chest X-ray images. Using medical pictures, often chest X-rays or CT scans, pneumonia illness classification includes the application of machine learning and deep learning algorithms to automatically distinguish between healthy and pneumonia-infected individuals. In impoverished nations where access to healthcare is poor, pneumonia is a major cause of illness and mortality.