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Keywords = neocoronal pneumonia

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32 pages, 3910 KB  
Article
An Analysis of Body Language of Patients Using Artificial Intelligence
by Rawad Abdulghafor, Abdelrahman Abdelmohsen, Sherzod Turaev, Mohammed A. H. Ali and Sharyar Wani
Healthcare 2022, 10(12), 2504; https://doi.org/10.3390/healthcare10122504 - 10 Dec 2022
Cited by 16 | Viewed by 7602
Abstract
In recent decades, epidemic and pandemic illnesses have grown prevalent and are a regular source of concern throughout the world. The extent to which the globe has been affected by the COVID-19 epidemic is well documented. Smart technology is now widely used in [...] Read more.
In recent decades, epidemic and pandemic illnesses have grown prevalent and are a regular source of concern throughout the world. The extent to which the globe has been affected by the COVID-19 epidemic is well documented. Smart technology is now widely used in medical applications, with the automated detection of status and feelings becoming a significant study area. As a result, a variety of studies have begun to focus on the automated detection of symptoms in individuals infected with a pandemic or epidemic disease by studying their body language. The recognition and interpretation of arm and leg motions, facial recognition, and body postures is still a developing field, and there is a dearth of comprehensive studies that might aid in illness diagnosis utilizing artificial intelligence techniques and technologies. This literature review is a meta review of past papers that utilized AI for body language classification through full-body tracking or facial expressions detection for various tasks such as fall detection and COVID-19 detection, it looks at different methods proposed by each paper, their significance and their results. Full article
(This article belongs to the Special Issue Artificial Intelligence Applications in Medicine)
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