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International Advanced Research Journal in Science, Engineering and Technology
International Advanced Research Journal in Science, Engineering and Technology A Monthly Peer-Reviewed Multidisciplinary Journal
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← Back to VOLUME 10, ISSUE 5, MAY 2023

Deep Learning Based Respiratory Sound Analysis for The Detection of Chronic Obstructive Pulmonary Disease

Mrs. Sowmya M, Nanditha V, Nithya J, Rakshitha J, Vyshnavi M R

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Abstract: Nearly one-quarter million Americans die with or of advanced chronic obstructive pulmonary disease (COPD) each year. Many patients die after a prolonged functional decline that is accompanied by much suffering. Though difficult prognostically and emotionally, the anticipation of death opens the door to planning and preparing for terminal care. Epidemiologists have begun to identify characteristics of COPD patients who are most likely to die within 6-12 months, including severe, irreversible airflow obstruction, severely impaired and declining exercise capacity and performance status, older age, concomitant cardiovascular or another comorbid disease, and a history of recent hospitalizations for acute care. Clinicians are encouraged to raise the difficult subject of planning for death when many of these characteristics apply. Patients with far-advanced diseases are often receptive to the recommendation of a dual agenda: "Hope for and expect the best, and prepare for the worst." Medical planning is best pursued in an out-patient office during a prescheduled, 3-way conversation between the patient, health care proxy, and physician. An advance directive can be written after the meeting to summarize the conversation. Clinicians should consider recommending hospice care when a COPD patient is at high risk of respiratory failure from the next chest infection and in need of frequent or specialized home care. Preparation for death should include a realistic appraisal of the prospects for dying peacefully at home and a contingency plan for terminal hospitalization, should the need arise.

Keywords: Chronic Obstructive Pulmonary Disease, irreversible airflow obstruction, concomitant cardiovascular.

How to Cite:

[1] Mrs. Sowmya M, Nanditha V, Nithya J, Rakshitha J, Vyshnavi M R, “Deep Learning Based Respiratory Sound Analysis for The Detection of Chronic Obstructive Pulmonary Disease,” International Advanced Research Journal in Science, Engineering and Technology (IARJSET), DOI: 10.17148/IARJSET.2023.10573

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