Multirole of the Internet of Medical Things (IoMT) in Biomedical Systems for Managing Smart Healthcare Systems: An Overview of Current and Future Innovative Trends
Identifikátory výsledku
Kód výsledku v IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F62156489%3A43210%2F24%3A43924656" target="_blank" >RIV/62156489:43210/24:43924656 - isvavai.cz</a>
Výsledek na webu
<a href="https://doi.org/10.1016/j.jiph.2024.01.013" target="_blank" >https://doi.org/10.1016/j.jiph.2024.01.013</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1016/j.jiph.2024.01.013" target="_blank" >10.1016/j.jiph.2024.01.013</a>
Alternativní jazyky
Jazyk výsledku
angličtina
Název v původním jazyce
Multirole of the Internet of Medical Things (IoMT) in Biomedical Systems for Managing Smart Healthcare Systems: An Overview of Current and Future Innovative Trends
Popis výsledku v původním jazyce
Internet of Medical Things (IoMT) is an emerging subset of Internet of Things (IoT), often called as IoT in healthcare, refers to medical devices and applications with internet connectivity, is exponentially gaining researchers' attention due to its wide-ranging applicability in biomedical systems for Smart Healthcare systems. IoMT facilitates remote health biomedical system and plays a crucial role within the healthcare industry to enhance precision, reliability, consistency and productivity of electronic devices used for various healthcare purposes. It comprises a conceptualized architecture for providing information retrieval strategies to extract the data from patient records using sensors for biomedical analysis and diagnostics against manifold diseases to provide cost-effective medical solutions, quick hospital treatments, and personalized healthcare. This article provides a comprehensive overview of IoMT with special emphasis on its current and future trends used in biomedical systems, such as deep learning, machine learning, blockchains, artificial intelligence, radio frequency identification, and industry 5.0.
Název v anglickém jazyce
Multirole of the Internet of Medical Things (IoMT) in Biomedical Systems for Managing Smart Healthcare Systems: An Overview of Current and Future Innovative Trends
Popis výsledku anglicky
Internet of Medical Things (IoMT) is an emerging subset of Internet of Things (IoT), often called as IoT in healthcare, refers to medical devices and applications with internet connectivity, is exponentially gaining researchers' attention due to its wide-ranging applicability in biomedical systems for Smart Healthcare systems. IoMT facilitates remote health biomedical system and plays a crucial role within the healthcare industry to enhance precision, reliability, consistency and productivity of electronic devices used for various healthcare purposes. It comprises a conceptualized architecture for providing information retrieval strategies to extract the data from patient records using sensors for biomedical analysis and diagnostics against manifold diseases to provide cost-effective medical solutions, quick hospital treatments, and personalized healthcare. This article provides a comprehensive overview of IoMT with special emphasis on its current and future trends used in biomedical systems, such as deep learning, machine learning, blockchains, artificial intelligence, radio frequency identification, and industry 5.0.
Klasifikace
Druh
J<sub>imp</sub> - Článek v periodiku v databázi Web of Science
CEP obor
—
OECD FORD obor
30304 - Public and environmental health
Návaznosti výsledku
Projekt
—
Návaznosti
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace
Ostatní
Rok uplatnění
2024
Kód důvěrnosti údajů
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Údaje specifické pro druh výsledku
Název periodika
Journal of Infection and Public Health
ISSN
1876-0341
e-ISSN
1876-035X
Svazek periodika
17
Číslo periodika v rámci svazku
4
Stát vydavatele periodika
NL - Nizozemsko
Počet stran výsledku
14
Strana od-do
559-572
Kód UT WoS článku
001187973800001
EID výsledku v databázi Scopus
2-s2.0-85185507500