Answering clinical questions using machine learning: should we look at diastolic blood pressure when tailoring blood pressure control?
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61384399%3A31140%2F22%3A00058479" target="_blank" >RIV/61384399:31140/22:00058479 - isvavai.cz</a>
Result on the web
<a href="https://www.mdpi.com/2077-0383/11/24/7454" target="_blank" >https://www.mdpi.com/2077-0383/11/24/7454</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.3390/jcm11247454" target="_blank" >10.3390/jcm11247454</a>
Alternative languages
Result language
angličtina
Original language name
Answering clinical questions using machine learning: should we look at diastolic blood pressure when tailoring blood pressure control?
Original language description
Main topics of the document: cardiovascular risk; diastolic blood pressure; machine learning; SPRINT trial
Czech name
—
Czech description
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Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
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Continuities
R - Projekt Ramcoveho programu EK
Others
Publication year
2022
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
Journal of clinical medicine
ISSN
2077-0383
e-ISSN
2077-0383
Volume of the periodical
11
Issue of the periodical within the volume
24
Country of publishing house
CH - SWITZERLAND
Number of pages
14
Pages from-to
"nestrankovano"
UT code for WoS article
000902484200001
EID of the result in the Scopus database
2-s2.0-85144727348