Open Access
Open access
Mendel, volume 27, issue 2, pages 80-89

A Systematic Review and Analysis on Deep Learning Techniques Used in Diagnosis of Various Categories of Lung Diseases

Dutta S.R., Vangipuram R., Jasthy S.
Publication typeJournal Article
Publication date2021-12-21
Journal: Mendel
scimago Q3
SJR0.302
CiteScore2.2
Impact factor
ISSN18033814, 25713701
Computational Mathematics
Theoretical Computer Science
General Computer Science
Abstract

One of the record killers in the world is lung disease. Lung disease denotes to many disorders affecting the lungs. These diseases can be identified through Chest X- Ray, Computed Tomography CT, Ultrasound tests. This study provides a systematic review on different types of Deep Learning (DL) designs, methods, techniques used by different researchers in diagnosing COVID-19, Pneumonia, Tuberculosis, Lung tumor, etc. In the present research study, a systematic review and analysis is carried by following PRISMA research methodology. For this study, more than 900 research articles are considered from various indexing sources such as Scopus and Web of Science. After several selection steps, finally a 40 quality research articles are included for detailed analysis. From this study, it is observed that majority of the research articles focused on DL techniques with Chest X-Ray images and few articles focused on CT scan images and very few have focused on Ultrasound images to identify the lung disease

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