Using machine learning to improve the diagnostic accuracy of the modified Duke/ESC 2015 criteria in patients with suspected prosthetic valve endocarditis – a proof of concept study

Λεπτομέρειες βιβλιογραφικής εγγραφής
Τίτλος:	Using machine learning to improve the diagnostic accuracy of the modified Duke/ESC 2015 criteria in patients with suspected prosthetic valve endocarditis – a proof of concept study
Συγγραφείς:	ten Hove, D.^{Aff1, Aff2, IDs0025902406774y_cor1}, Slart, R. H. J. A.^{Aff1, Aff3}, Glaudemans, A. W. J. M.^Aff1, Postma, D. F.^Aff4, Gomes, A.^Aff2, Swart, L. E.^Aff5, Tanis, W.^Aff6, Geel, P. P. van^Aff7, Mecozzi, G.^Aff8, Budde, R. P. J.^Aff9, Mouridsen, K.^{Aff1, Aff10}, Sinha, B.^Aff2
Πηγή:	European Journal of Nuclear Medicine and Molecular Imaging. 51(13):3924-3933
Βάση Δεδομένων:	Springer Nature Journals

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