Deep Learning-Based Approach to Classify Pneumonia on Chest Radiographs

Aron Hernandez Trinidad, Teodoro Cordova Fraga, Rafael Guzman Cabrera and Blanca O Murillo Ortiz
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Teodoro Cordova Fraga: Physical & Engineering Department-DCI, University of Guanajuato campus Leon, Mexico
Rafael Guzman Cabrera: Engineering Division, University of Guanajuato, Mexico
Blanca O Murillo Ortiz: IMSS High Specialty Medical Unit, T1 Clinic, Mexico

Biomedical Journal of Scientific & Technical Research, 2024, vol. 59, issue 3, 51563-51571

Abstract: The diagnosis of pneumonia by X-rays is a widespread practice in the early detection of the disease and initiation of timely treatment. Automatic classification models using convolutional neural networks (CNN) have proven to be an effective and accurate tool in the diagnosis of this disease. A model that detects pneumonia in a set of chest X-rays, using two CNNs: ResNet50 & VGG16 is proposed in this work.

Keywords: Journals on Medical Drug and Therapeutics; Journals on Emergency Medicine; Physical Medicine and Rehabilitation; Journals on Infectious Diseases Addiction Science and Clinical Pathology; Open Access Clinical and Medical Journal; Journals on Biomedical Science; List of Open Access Medical Journal; Journals on Biomedical Engineering; Open Access Medical Journal; Biomedical Science Articles; Journal of Scientific and Technical Research (search for similar items in EconPapers)
Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:abf:journl:v:59:y:2024:i:3:p:51563-51571

DOI: 10.26717/BJSTR.2024.59.009298

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