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Data processing pipeline for cardiogenic shock prediction using machine learning
- 1.0571168 - ÚI 2024 RIV CH eng J - Journal Article
Jajcay, Nikola - Bezák, B. - Segev, A. - Matetzky, S. - Janková, J. - Spartalis, M. - El Tahlawi, M. - Guerra, F. - Friebel, J. - Thevathasan, T. - Berta, I. - Pölzl, L. - Nägele, F. - Pogran, E. - Cader, F. A. - Jarakovic, M. - Gollmann-Tepeköylü, C. - Kollárová, M. - Petríková, K. - Tica, O. - Krychtiuk, K. A. - Tavazzi, G. - Skurk, C. - Huber, K. - Böhm, A.
Data processing pipeline for cardiogenic shock prediction using machine learning.
Frontiers in Cardiovascular Medicine. Roč. 10, 23 March 2023 (2023), č. článku 1132680. ISSN 2297-055X. E-ISSN 2297-055X
Institutional support: RVO:67985807
Keywords : classification * machine learning * missing data imputation * processing pipeline * prediction model * cardiogenic shock
OECD category: Cardiac and Cardiovascular systems
Impact factor: 2.8, year: 2023 ; AIS: 0.804, rok: 2023
Method of publishing: Open access
Result website:
https://dx.doi.org/10.3389/fcvm.2023.1132680DOI: https://doi.org/10.3389/fcvm.2023.1132680
Permanent Link: https://hdl.handle.net/11104/0342448File Download Size Commentary Version Access 0571168-aoa.pdf 1 5.1 MB OA CC BY 4.0 Publisher’s postprint open-access
Number of the records: 1
