Please use this identifier to cite or link to this item: doi:10.22028/D291-46245
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Title: microRNA neural networks improve diagnosis of acute coronary syndrome (ACS)
Author(s): Kayvanpour, Elham
Gi, Weng-Tein
Sedaghat-Hamedani, Farbod
Lehmann, David H.
Frese, Karen S.
Haas, Jan
Tappu, Rewati
Samani, Omid Shirvani
Nietsch, Rouven
Kahraman, Mustafa
Fehlmann, Tobias
Müller-Hennessen, Matthias
Weis, Tanja
Giannitsis, Evangelos
Niederdränk, Torsten
Keller, Andreas
Katus, Hugo A.
Meder, Benjamin
Language: English
Title: Journal of Molecular and Cellular Cardiology
Volume: 151 (2021)
Pages: 155-162
Publisher/Platform: Elsevier
Year of Publication: 2020
Free key words: Acute coronary syndrome
microRNA
Deep learning
High-sensitive troponin
DDC notations: 610 Medicine and health
Publikation type: Journal Article
DOI of the first publication: 10.1016/j.yjmcc.2020.04.014
URL of the first publication: https://doi.org/10.1016/j.yjmcc.2020.04.014
Link to this record: urn:nbn:de:bsz:291--ds-462451
hdl:20.500.11880/40538
http://dx.doi.org/10.22028/D291-46245
ISSN: 0022-2828
Date of registration: 10-Sep-2025
Description of the related object: Supplementary data
Related object: https://ars.els-cdn.com/content/image/1-s2.0-S0022282820300973-mmc1.pptx
https://ars.els-cdn.com/content/image/1-s2.0-S0022282820300973-mmc2.docx
https://ars.els-cdn.com/content/image/1-s2.0-S0022282820300973-mmc3.docx
Faculty: M - Medizinische Fakultät
Department: M - Medizinische Biometrie, Epidemiologie und medizinische Informatik
Professorship: M - Univ.-Prof. Dr. Andreas Keller
Collections:SciDok - Der Wissenschaftsserver der Universität des Saarlandes

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