AI Approaches for Pulmonary Disease Forecast

There is a significant risk to the healthcare system that respiratory diseases will become the leading cause of mortality globally by 2030. Recent advancements in artificial intelligence (AI) techniques intended to identify and categorize a range of respiratory ailments have drawn considerable inter...

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Bibliographic Details
Published in2023 International Conference on Advances in Computation, Communication and Information Technology (ICAICCIT) pp. 944 - 949
Main Authors Mishra, Awakash, Ganguly, Saurav, C, Sandeep Kumar
Format Conference Proceeding
LanguageEnglish
Published IEEE 23.11.2023
Subjects
Airway Disorders
Artificial Intelligence
Atmospheric modeling
Deep learning
Diagnosis
Healthcare
Machine Learning
Medical services
Prediction
Pulmonary diseases
Respiratory Illnesses
Reviews
System performance
Systematic Review and Medical Research
Systematics
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Summary:There is a significant risk to the healthcare system that respiratory diseases will become the leading cause of mortality globally by 2030. Recent advancements in artificial intelligence (AI) techniques intended to identify and categorize a range of respiratory ailments have drawn considerable interest from the scientific community. This comprehensive study aims to provide an overview of the most current machine learning and deep learning techniques especially developed for the identification of airway illnesses. It also forecasts future developments in this discipline by examining present problems and suggesting possible lines of inquiry. Our thorough analysis comprises 155 publications that describe various respiratory illnesses, highlighting the crucial role that machine learning methods play in forecasting certain ailments. As a result, this study outlines the challenges that now exist and the opportunities for future advancement while also highlighting the potential benefits of machine learning and artificial intelligence (AI) in enhancing the efficacy of apps for diagnosing respiratory illnesses.
DOI:10.1109/ICAICCIT60255.2023.10465790