Please use this identifier to cite or link to this item: http://hdl.handle.net/20.500.12188/29764
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dc.contributor.authorKostoska, Magdalenaen_US
dc.contributor.authorKuzmanov, Ivanen_US
dc.contributor.authorKoteska, Bojanaen_US
dc.contributor.authorLehocki, Fedoren_US
dc.contributor.authorMadevska Bogdanova, Anaen_US
dc.date.accessioned2024-03-18T06:42:23Z-
dc.date.available2024-03-18T06:42:23Z-
dc.date.issued2024-
dc.identifier.urihttp://hdl.handle.net/20.500.12188/29764-
dc.description.abstractThe development of non-invasive easily available blood pres- sure estimation methods using electrocardiogram - ECG and/or photo- plethysmogram - PPG signals has gained increasing attention. However, there is a lack of consistency in the evaluation of these methods due to variations in the size and availability of data in published datasets. Our research involves retrieving, cleaning, and storing a portion of the MIMIC-III database for utilization in model training and testing. This paper outlines our methodology for processing the MIMIC-III database, along with the challenges encountered during the process.en_US
dc.description.sponsorshipNATO SPSen_US
dc.description.sponsorshipFaculty of Computer Science and Engineering, Ss. Cyril and Methodius Universityen_US
dc.language.isoen_USen_US
dc.relationSmart Patch for Life Support Systems - SP4LIFEen_US
dc.relationIBS4LIFEen_US
dc.relation.ispartofseries;142-152-
dc.subjectMIMIC-IIIen_US
dc.subjectelectrocardiogramen_US
dc.subjectphotoplethysmogramen_US
dc.subjectblood pressure estimationen_US
dc.subjectartificial neural networken_US
dc.subjectdeep learningen_US
dc.titleProcessing MIMIC-III for Evaluation of Various Blood Pressure Estimation Modelsen_US
dc.typeProceeding articleen_US
dc.relation.conferenceICT Innovations 2023en_US
item.grantfulltextopen-
item.fulltextWith Fulltext-
crisitem.author.deptFaculty of Computer Science and Engineering-
crisitem.author.deptFaculty of Computer Science and Engineering-
crisitem.author.deptFaculty of Computer Science and Engineering-
Appears in Collections:Faculty of Computer Science and Engineering: Conference papers
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