Artificial Intelligence Can Improve Patient Management at the Time of a Pandemic: The Role of Voice Technology

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00159816%3A_____%2F21%3A00075233" target="_blank" >RIV/00159816:_____/21:00075233 - isvavai.cz</a>

Result on the web

<a href="https://www.jmir.org/2021/5/e22959" target="_blank" >https://www.jmir.org/2021/5/e22959</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.2196/22959" target="_blank" >10.2196/22959</a>

Result language

angličtina

Original language name

Artificial Intelligence Can Improve Patient Management at the Time of a Pandemic: The Role of Voice Technology

Original language description

Artificial intelligence-driven voice technology deployed on mobile phones and smart speakers has the potential to improve patient management and organizational workflow. Voice chatbots have been already implemented in health care-leveraging innovative telehealth solutions during the COVID-19 pandemic. They allow for automatic acute care triaging and chronic disease management, including remote monitoring, preventive care, patient intake, and referral assistance. This paper focuses on the current clinical needs and applications of artificial intelligence-driven voice chatbots to drive operational effectiveness and improve patient experience and outcomes.

Czech name

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Czech description

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Type

J_imp - Article in a specialist periodical, which is included in the Web of Science database

CEP classification

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OECD FORD branch

30300 - Health sciences

Project

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Continuities

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Publication year

2021

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Name of the periodical

JOURNAL OF MEDICAL INTERNET RESEARCH

ISSN

1438-8871

e-ISSN

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Volume of the periodical

23

Issue of the periodical within the volume

5

Country of publishing house

CA - CANADA

Number of pages

11

Pages from-to

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UT code for WoS article

000655696700002

EID of the result in the Scopus database

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