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Artificial Intelligence and technology in COVID Era: A narrative review
Application of artificial intelligence (AI) in the medical field during the coronavirus disease 2019 (COVID-19) era is being explored further due to its beneficial aspects such as self-reported data analysis, X-ray interpretation, computed tomography (CT) image recognition, and patient management. T...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Wolters Kluwer - Medknow
2021
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8174437/ https://www.ncbi.nlm.nih.gov/pubmed/34103818 http://dx.doi.org/10.4103/joacp.JOACP_558_20 |
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author | Ahuja, Vanita Nair, Lekshmi V. |
author_facet | Ahuja, Vanita Nair, Lekshmi V. |
author_sort | Ahuja, Vanita |
collection | PubMed |
description | Application of artificial intelligence (AI) in the medical field during the coronavirus disease 2019 (COVID-19) era is being explored further due to its beneficial aspects such as self-reported data analysis, X-ray interpretation, computed tomography (CT) image recognition, and patient management. This narrative review article included published articles from MEDLINE/PubMed, Google Scholar and National Informatics Center egov mobile apps. The database was searched for “Artificial intelligence” and “COVID-19” and “respiratory care unit” written in the English language during a period of one year 2019-2020. The relevance of AI for patients is in hands of people with digital health tools, Aarogya setu app and Smartphone technology. AI shows about 95% accuracy in detecting COVID-19-specific chest findings. Robots with AI are being used for patient assessment and drug delivery to patients to avoid the spread of infection. The pandemic outbreak has replaced the classroom method of teaching with the online execution of teaching practices and simulators. AI algorithms have been used to develop major organ tissue characterization and intelligent pain management techniques for patients. The Blue-dot AI-based algorithm helps in providing early warning signs. The AI model automatically identifies a patient in respiratory distress based on face detection, face recognition, facial action unit detection, expression recognition, posture, extremity movement analysis, visitation frequency detection sound pressure, and light level detection. There is now no looking back as AI and machine learning are to stay in the field of training, teaching, patient care, and research in the future. |
format | Online Article Text |
id | pubmed-8174437 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Wolters Kluwer - Medknow |
record_format | MEDLINE/PubMed |
spelling | pubmed-81744372021-06-07 Artificial Intelligence and technology in COVID Era: A narrative review Ahuja, Vanita Nair, Lekshmi V. J Anaesthesiol Clin Pharmacol Review Article Application of artificial intelligence (AI) in the medical field during the coronavirus disease 2019 (COVID-19) era is being explored further due to its beneficial aspects such as self-reported data analysis, X-ray interpretation, computed tomography (CT) image recognition, and patient management. This narrative review article included published articles from MEDLINE/PubMed, Google Scholar and National Informatics Center egov mobile apps. The database was searched for “Artificial intelligence” and “COVID-19” and “respiratory care unit” written in the English language during a period of one year 2019-2020. The relevance of AI for patients is in hands of people with digital health tools, Aarogya setu app and Smartphone technology. AI shows about 95% accuracy in detecting COVID-19-specific chest findings. Robots with AI are being used for patient assessment and drug delivery to patients to avoid the spread of infection. The pandemic outbreak has replaced the classroom method of teaching with the online execution of teaching practices and simulators. AI algorithms have been used to develop major organ tissue characterization and intelligent pain management techniques for patients. The Blue-dot AI-based algorithm helps in providing early warning signs. The AI model automatically identifies a patient in respiratory distress based on face detection, face recognition, facial action unit detection, expression recognition, posture, extremity movement analysis, visitation frequency detection sound pressure, and light level detection. There is now no looking back as AI and machine learning are to stay in the field of training, teaching, patient care, and research in the future. Wolters Kluwer - Medknow 2021 2021-04-10 /pmc/articles/PMC8174437/ /pubmed/34103818 http://dx.doi.org/10.4103/joacp.JOACP_558_20 Text en Copyright: © 2021 Journal of Anaesthesiology Clinical Pharmacology https://creativecommons.org/licenses/by-nc-sa/4.0/This is an open access journal, and articles are distributed under the terms of the Creative Commons Attribution-NonCommercial-ShareAlike 4.0 License, which allows others to remix, tweak, and build upon the work non-commercially, as long as appropriate credit is given and the new creations are licensed under the identical terms. |
spellingShingle | Review Article Ahuja, Vanita Nair, Lekshmi V. Artificial Intelligence and technology in COVID Era: A narrative review |
title | Artificial Intelligence and technology in COVID Era: A narrative review |
title_full | Artificial Intelligence and technology in COVID Era: A narrative review |
title_fullStr | Artificial Intelligence and technology in COVID Era: A narrative review |
title_full_unstemmed | Artificial Intelligence and technology in COVID Era: A narrative review |
title_short | Artificial Intelligence and technology in COVID Era: A narrative review |
title_sort | artificial intelligence and technology in covid era: a narrative review |
topic | Review Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8174437/ https://www.ncbi.nlm.nih.gov/pubmed/34103818 http://dx.doi.org/10.4103/joacp.JOACP_558_20 |
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