Data di Pubblicazione:
2022
Abstract:
In this work we present the creation of a large, structured database of CardioTocoGraphic (CTG) recordings, starting from a raw dataset containing tracings collected between 2013 and 2021 by the medical team of the University Hospital Federico II of Naples. The aim of the work is to provide a big, structured database of real clinical cardiotocographic data, useful for subsequent processing and analysis through state-of-the-art methods, in particular Deep Learning Methods. This organized dataset could lead to an increase of the diagnostic accuracy of CTG analysis in the discrimination of healthy and unhealthy fetuses.
Tipologia CRIS:
4.1 Contributo in Atti di convegno
Elenco autori:
Spairani, E.; Daniele, B.; Magenes, G.; Signorini, M. G.
Link alla scheda completa:
Titolo del libro:
Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS