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Machine learning based SpO2 prediction from PPG signal's characteristics features
Title Machine learning based SpO2 prediction from PPG signal's characteristics features. textový dokument (print) Author Koteska B. Co-authors Mitrova H. Madevska Bogdanova A. Lehocki Fedor 1976 SAVMER - Ústav merania SAV SCOPUS RID ORCID Source document 2022 IEEE International Symposium on Medical Measurements and Applications (MeMeA) Proceedings. P. non. - [s.l.] : IEEE, 2022 ; IEEE International Symposium on Medical Measurements and Applications (MeMeA 2022) Language eng - English Country US - United States of America Document kind rozpis článkov z periodík (rbx) Citations HU, M. - WU, X. - WANG, X.H. - XING, Y. - AN, N. - SHI, P. Contactless blood oxygen estimation from face videos: A multi-model fusion method based on deep learning. In BIOMEDICAL SIGNAL PROCESSING AND CONTROL. ISSN 1746-8094, MAR 2023, vol. 81. Dostupné na: https://doi.org/10.1016/j.bspc.2022.104487. BALARAMAN, K. - CLARET, S.P.A. Hybrid ResNet and Bidirectional LSTM based Deep Learning Model for Cardiovascular Disease Detection using PPG Signals. In JOURNAL OF MACHINE AND COMPUTING, 2023, vol. 3, no. 3, p. 351-359. ISSN 2789-1801. Dostupné na: https://doi.org/10.53759/7669/jmc202303030. Category ADMB - Scientific papers in foreign non-impacted journals registered in Web of Sciences or Scopus Category of document (from 2022) V2 - Vedecký výstup publikačnej činnosti ako časť editovanej knihy alebo zborníka Type of document príspevok z podujatia Year 2022 Registered in WOS Registered in SCOPUS DOI 10.1109/MeMeA54994.2022.9856498 article
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Number of the records: 1