Electrocardiogram-based mortality prediction in patients with COVID-19 using machine learning

Autor: van de Leur, R. R., Bleijendaal, H., Taha, K., Mast, T., Gho, J. M. I. H., Linschoten, M., van Rees, B., Henkens, M. T. H. M., Heymans, S., Sturkenboom, N., Tio, R. A., Offerhaus, J. A., Bor, W. L., Maarse, M., Haerkens-Arends, H. E., Kolk, M. Z. H., van der Lingen, A. C. J., Selder, J. J., Wierda, E. E., van Bergen, P. F. M. M., Winter, M. M., Zwinderman, A. H., Doevendans, P. A., van der Harst, P., Pinto, Y. M., Asselbergs, F. W., van Es, R., Tjong, F. V. Y.

Publikováno v: Netherlands Heart Journal, 30(6), 312-318. Bohn Stafleu van Loghum
Netherlands heart journal, 30(6), 312-318. Bohn Stafleu van Loghum
the CAPACITY-COVID collaborative consortium 2022, ' Electrocardiogram-based mortality prediction in patients with COVID-19 using machine learning ', Netherlands Heart Journal, vol. 30, no. 6, pp. 312-318 . https://doi.org/10.1007/s12471-022-01670-2

Background and purpose The electrocardiogram (ECG) is frequently obtained in the work-up of COVID-19 patients. So far, no study has evaluated whether ECG-based machine learning models have added value to predict in-hospital mortality specifically in

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e43c0cd8031ca70983fe1c71270fc1e3
https://pubmed.ncbi.nlm.nih.gov/35301688