Please use this identifier to cite or link to this item: doi:10.22028/D291-44701
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Title: Artificial Intelligence-Derived Risk Prediction: A Novel Risk Calculator Using Office and Ambulatory Blood Pressure
Author(s): Guimarães, Pedro
Keller, Andreas
Böhm, Michael
Lauder, Lucas
Fehlmann, Tobias
Ruilope, Luis M.
Vinyoles, Ernest
Gorostidi, Manuel
Segura, Julián
Ruiz-Hurtado, Gema
Staplin, Natalie
Williams, Bryan
de la Sierra, Alejandro
Mahfoud, Felix
Language: English
Title: Hypertension
Volume: 82 (2025)
Issue: 1
Pages: 46-56
Publisher/Platform: Wolters Kluwer
Year of Publication: 2024
Free key words: blood pressure
artificial intelligence
machine learning
neural networks, computer
risk factors
DDC notations: 610 Medicine and health
Publikation type: Journal Article
DOI of the first publication: 10.1161/HYPERTENSIONAHA.123.22529
URL of the first publication: https://doi.org/10.1161/HYPERTENSIONAHA.123.22529
Link to this record: urn:nbn:de:bsz:291--ds-447011
hdl:20.500.11880/39814
http://dx.doi.org/10.22028/D291-44701
ISSN: 1524-4563
0194-911X
Date of registration: 18-Mar-2025
Description of the related object: Supplemental Material
Related object: https://www.ahajournals.org/doi/suppl/10.1161/HYPERTENSIONAHA.123.22529/suppl_file/hyp_hype-2023-22529-t_supp2.docx
Faculty: M - Medizinische Fakultät
Department: M - Innere Medizin
M - Medizinische Biometrie, Epidemiologie und medizinische Informatik
Professorship: M - Prof. Dr. Michael Böhm
M - Univ.-Prof. Dr. Andreas Keller
Collections:SciDok - Der Wissenschaftsserver der Universität des Saarlandes

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