Title: An effective review on the prediction and analysis of infectious lung diseases using machine learning algorithms

Authors: V. Indira; D. Annal Priyadarshini; R. Geetha; V. Sujatha

Addresses: Department of Computer Science and Engineering, Alpha College of Engineering, Chennai-600124, India ' Department of Computer Science and Engineering, S.A. Engineering College, Chennai-600077, India ' Department of Computer Science and Engineering, S.A. Engineering College, Chennai-600077, India ' Department of Master of Computer Applications, S.A. Engineering College, Chennai-600077, India

Abstract: Lung diseases are very seriously increasing nowadays due to the rapid environmental changes and the variety of viruses in the universe. This review focuses on using machine learning and deep learning algorithms to predict and analyse lung cancer, tuberculosis, coronavirus disease 2019 (COVID-19), influenza, asthma, and chronic obstructive pulmonary disease (COPD). In this paper, machine learning and deep learning models are used to analyse the affected lung mortality and have decreased the amount of physical work needed. This paper inspects how numerous machine-learning algorithms can be used to discover many lung states. The main aim of this review is to envision several tempers in lung disease to analyse using machine learning and diagnose the survival issue and the domain's feasible future. In addition, this examines the accuracy and efficiency of machine learning and deep learning categorises lung disease with minimal possible error.

Keywords: machine learning; ML; deep learning; computer vision; lung disease.

DOI: 10.1504/IJBRA.2024.139999

International Journal of Bioinformatics Research and Applications, 2024 Vol.20 No.3, pp.205 - 228

Received: 06 Jul 2023
Accepted: 25 Sep 2023
Published online: 15 Jul 2024 *

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