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.

A Novel Large Structured Cardiotocographic Database

Spairani E.
Writing – Original Draft Preparation
;
Magenes G.
Writing – Review & Editing
;
2022-01-01

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.
2022
Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS
Inglese
44th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2022
2022
gbr
2022-
1375
1378
4
978-1-7281-2782-8
Institute of Electrical and Electronics Engineers Inc.
no
none
Spairani, E.; Daniele, B.; Magenes, G.; Signorini, M. G.
273
info:eu-repo/semantics/conferenceObject
4
4 Contributo in Atti di Convegno (Proceeding)::4.1 Contributo in Atti di convegno
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11571/1483399
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