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Search: L773:0907 4449 OR L773:1399 0047 > (1995-1999) > An intelligent tele...

An intelligent telemonitoring application for coronavirus patients : reCOVeryaID

D'Auria, Daniela (author)
Faculty of Engineering, Free University of Bozen-Bolzano, Bolzano, Italy
Russo, Raffaele (author)
Pineta Grande Hospital, Caserta, Italy
Fedele, Alfonso (author)
University Riuniti Hospital, Ancona, Italy
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Addabbo, Federica (author)
Kronosan Srl, Montevergine Hospital, Mercogliano, Italy
Calvanese, Diego (author)
Umeå universitet,Institutionen för datavetenskap,Faculty of Engineering, Free University of Bozen-Bolzano, Bolzano, Italy
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 (creator_code:org_t)
Frontiers Media S.A. 2023
2023
English.
In: Frontiers in Big Data. - : Frontiers Media S.A.. - 2624-909X. ; 6
  • Journal article (peer-reviewed)
Abstract Subject headings
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  • The COVID-19 emergency underscored the importance of resolving crucial issues of territorial health monitoring, such as overloaded phone lines, doctors exposed to infection, chronically ill patients unable to access hospitals, etc. In fact, it often happened that people would call doctors/hospitals just out of anxiety, not realizing that they were clogging up communications, thus causing problems for those who needed them most; such people, often elderly, have often felt lonely and abandoned by the health care system because of poor telemedicine. In addition, doctors were unable to follow up on the most serious cases or make sure that others did not worsen. Thus, uring the first pandemic wave we had the idea to design a system that could help people alleviate their fears and be constantly monitored by doctors both in hospitals and at home; consequently, we developed reCOVeryaID, a telemonitoring application for coronavirus patients. It is an autonomous application supported by a knowledge base that can react promptly and inform medical doctors if dangerous trends in the patient's short- and long-term vital signs are detected. In this paper, we also validate the knowledge-base rules in real-world settings by testing them on data from real patients infected with COVID-19.

Subject headings

NATURVETENSKAP  -- Data- och informationsvetenskap -- Datavetenskap (hsv//swe)
NATURAL SCIENCES  -- Computer and Information Sciences -- Computer Sciences (hsv//eng)
MEDICIN OCH HÄLSOVETENSKAP  -- Hälsovetenskap -- Hälso- och sjukvårdsorganisation, hälsopolitik och hälsoekonomi (hsv//swe)
MEDICAL AND HEALTH SCIENCES  -- Health Sciences -- Health Care Service and Management, Health Policy and Services and Health Economy (hsv//eng)

Keyword

artificial intelligence
coronavirus
COVID-19
eHealth
long-term monitoring
rule-based system
telehealth
telemedicine

Publication and Content Type

ref (subject category)
art (subject category)

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