AI-DRIVEN INNOVATIONS IN RESPIRATORY MEDICINE: ENHANCING DIAGNOSTIC ACCURACY AND PREDICTING FUTURE RISKS
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Keywords
Artificial Intelligence, Respiratory medicine, Chronic obstructive pulmonary disease COPD, asthmatic patients, Machine learning (ML)
Abstract
The use of AI in diagnosing respiratory diseases has become more prominent due to key progresses made in AI technology and its effects on diagnostics and their outcomes. The purpose of this research is to review the applicability of AI tools for COPD, asthma, and other respiratory disorders concerning diagnostics and profiling. The approach that has been adopted was a quantitative method with the analysis of the performance based on data from EHRs, patient registries, and past trials. Different learning algorithms including the kernel-based SVM, RF, deep learning algorithms including the CNNs and RNNs were built and trained. The measures of success were given by the number of true and false positives, true and false negatives, and the AUC. In the analysis of the models applied, the highest percentage of accuracy was recorded with CNN at 95% with a difference of 0% from VGG-16 and an AUC of 0. 92 concerning chest X-ray diagnosis. CNNs also attained a short-term risk prediction AUC of 0. 93, and RNNs had the best prediction of long-term risk with the AUC of 0. 90. In comparison to conventional approaches, AI models were found to be more effective in most cases, specifically, in the identification of early-stage diseases and creating risk assessment. The results are positive although the methodology faces certain difficulties like variability of data and implementation of the method into practice. This paper discusses the changes that AI has brought to respiratory medicine and shows how future developments can help overcome existing difficulties and increase the use of AI.
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This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
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Dr. Siddharth Arjun Atwal
JR, Department of Internal Medicine, Punjab Institute of Medical sciences
Saurabh Mangla
Mbbs, Senior Drug Safety Physician, Workplace: Parexel International
Dr Aditya Hans
Medical Intern, College: GMCH 32, Chandigarh,
Dr Abanibhusan Jena
Associate, Professor, Fakir Mohan, Medical College, Balesore FM University, Balesore and Odisha University of Health Sciences, Bhubaneswar MBBS, MD, FCCM,