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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Published in | 2023 International Conference on Advances in Computation, Communication and Information Technology (ICAICCIT) pp. 944 - 949 |
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Main Authors | , , |
Format | Conference Proceeding |
Language | English |
Published |
IEEE
23.11.2023
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Subjects | |
Online Access | Get full text |
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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. |
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DOI: | 10.1109/ICAICCIT60255.2023.10465790 |