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Title of Journal: Med Bio Eng Comput

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Abbravation: Medical & Biological Engineering & Computing

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Springer-Verlag

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DOI

10.1016/0022-2852(74)90170-2

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1741-0444

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An informative probability model enhancing real ti

Authors: G Cevenini F M Severi C Bocchi F Petraglia P Barbini
Publish Date: 2008/01/10
Volume: 46, Issue: 2, Pages: 109-120
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Abstract

A multinormal probability model is proposed to correct human errors in fetal echobiometry and improve the estimation of fetal weight EFW Model parameters were designed to depend on major pregnancy data and were estimated through feedforward artificial neural networks ANNs Data from 4075 women in labour were used for training and testing ANNs The model was implemented numerically to provide EFW together with probabilities of congruence among measured echobiometric parameters It enabled ultrasound measurement errors to be realtime checked and corrected interactively The software was useful for training medical staff and standardizing measurement procedures It provided multiple statistical data on fetal morphometry and aid for clinical decisions A clinical protocol for testing the system ability to detect measurement errors was conducted with 61 women in the last week of pregnancy It led to decisive improvements in EFW accuracy

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