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10.4103/joacp.JOACP_558_20 http://scihub22266oqcxt.onion/10.4103/joacp.JOACP_558_20 34103818!8174437!34103818     free     free     free Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       J+Anaesthesiol+Clin+Pharmacol 2021 ; 37 (1): 28-34 Nephropedia Template TP {{tp|p=34103818|t=2021. Artificial Intelligence and technology in COVID Era: A narrative review |pdf=|usr=}}{{34103818}} gab.com Text Artificial Intelligence and technology in COVID Era: A narrative review JO: J Anaesthesiol Clin Pharmacol http://www.kidney.de/pget.php?&tw=1&pmid=34103818 #FOAvip 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. Twit Text FOAVip Artificial Intelligence and technology in COVID Era: A narrative review ????J Anaesthesiol Clin Pharmacol http://www.kidney.de/pget.php?&tw=1&pmid=34103818 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=34103818 #FOAvip English Wikipedia <ref>{{Cite pmid|34103818}}</ref> Artificial Intelligence and technology in COVID Era: A narrative review #MMPMID34103818 Ahuja V; Nair LV J Anaesthesiol Clin Pharmacol 2021[Jan]; 37 (1): 28-34 PMID34103818show ga 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. äArtificial Intelligence and technology in COVID Era: A narrative revie(epmc).pdf DeepDyve Pubget Overpricing