Please use this identifier to cite or link to this item:
http://hdl.handle.net/20.500.12188/30467
DC Field | Value | Language |
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dc.contributor.author | Kostoska, Magdalena | en_US |
dc.contributor.author | Kuzmanov, Ivan | en_US |
dc.contributor.author | Koteska, Bojana | en_US |
dc.contributor.author | Lehocki, Fedor | en_US |
dc.contributor.author | Madevska Bogdanova, Ana | en_US |
dc.date.accessioned | 2024-06-07T07:45:24Z | - |
dc.date.available | 2024-06-07T07:45:24Z | - |
dc.date.issued | 2023-10 | - |
dc.identifier.uri | http://hdl.handle.net/20.500.12188/30467 | - |
dc.description.abstract | The development of non-invasive easily available blood pressure estimation methods using electrocardiogram - ECG and/or photoplethysmogram - 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.subject | MIMIC-III · electrocardiogram · photoplethysmogram · blood pressure estimation · artificial neural network · deep learning. | en_US |
dc.title | Processing MIMIC-III for Evaluation of Various Blood Pressure Estimation Models | en_US |
dc.type | Proceedings | en_US |
dc.relation.conference | ICT Innovations, 24-26 September, 2023, Ohrid, N. Macedonia | en_US |
item.fulltext | With Fulltext | - |
item.grantfulltext | open | - |
crisitem.author.dept | Faculty of Computer Science and Engineering | - |
crisitem.author.dept | Faculty of Computer Science and Engineering | - |
Appears in Collections: | Faculty of Computer Science and Engineering: Conference papers |
Files in This Item:
File | Description | Size | Format | |
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processing-mimic-iii-for-evaluation-of-various-blood-pressure-estimation-models.pdf | 369.62 kB | Adobe PDF | View/Open |
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