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Publication: IIP Proceedings Year: 2022, Month: November Page No: 69-80, ISSN/ISBN: 978-93-95632-81-2, DOI/Link: https://rsquarel.org/assets/docupload/rsl2023BAB412573725C84.pdf
INSIGHTS OF MEDICAL PRACTITIONERS ON UTILIZING ARTIFICIAL INTELLIGENCE TECHNOLOGY FOR DIAGNOSING RESPIRATORY DISEASES
Area/Stream: Artificial Intelligence, Authors: Dr. S. Sangeetha, Dr. J. Prabhakaran, Sakthivel P, Parthiban Shanmugam Keywords: Artificial Intelligence, deep learning, machine learning, X-Ray, Respiratory Medicine. Book Name /series: Futuristic Trends in Artificial Intelligence, Volume 2, Book 17, Part 1, Chapter 8Publication: IIP Proceedings Year: 2022, Month: November Page No: 69-80, ISSN/ISBN: 978-93-95632-81-2, DOI/Link: https://rsquarel.org/assets/docupload/rsl2023BAB412573725C84.pdf
Abstract:
Although the utilization of artificial intelligence (AI) in respiratory diseases care has been growing, there seems still many implementation issues. The purpose of this research is to investigate how medical professionals feel about the use of AI tools, as well as to investigate the many difficulties associated with putting these tools into practise in the context of diagnosing and treating respiratory disorders in tertiary care settings. At Tamil Nadu's tertiary care hospitals, a mixed method of research was carried out with 104 medical practitioners chosen randomly. The quantitative data were gathered using a semi-structured schedule. The two narrowly focused group talks executed for brainstorming (FGD) and analysed using the descriptive and qualitative statistical measures. Among all, 67.3 % concurred that AI can be applied in respiratory medicine, and 69.4% perceived AI implementation hurdles.
Cite this: Dr. S. Sangeetha, Dr. J. Prabhakaran, Sakthivel P, Parthiban Shanmugam ,"INSIGHTS OF MEDICAL PRACTITIONERS ON UTILIZING ARTIFICIAL INTELLIGENCE TECHNOLOGY FOR DIAGNOSING RESPIRATORY DISEASES", Futuristic Trends in Artificial Intelligence, Volume 2, Book 17, Part 1, Chapter 8, November, 2022, 69-80, 978-93-95632-81-2, https://rsquarel.org/assets/docupload/rsl2023BAB412573725C84.pdf
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