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http://hdl.handle.net/10609/134366
Title: | Caracterització i detecció precoç de la ventriculomegalia aïllada a partir de dades pre i post-natals |
Author: | Bosch Garcia, Meritxell |
Tutor: | Bonet-Carne, Elisenda Burgos-Artizzu, Xavier Paolo |
Others: | Prados Carrasco, Ferran |
Abstract: | Ventriculomegaly (VMG) is a rare disease that affects between 0.3 and 22 out of every 1000 pregnancies. 25-60% of these are isolated cases, which means that it has no other associated pathology. The evolution of the disease and the effect on neurodevelopment is not predictable. The detection of VMG is done through the measurement of only two parameters: the size of the Left Atrium and the Right Atrium. The aim is to use a database of 81 participants (41 affected and 40 unaffected) to improve characterisation of the condition and the prognosis and to provide an early detection to predict postnatal effects based on the available prenatal data. The small size of the database has been a challenge to find new characterisations of the disease, although some correlation has been detected between VMG and two other parameters: the Left Anterior Horn and the Right Anterior Horn. A binary classification model has been trained with a value of F1 of about 90%. This has been achieved applying neural networks or by cascading neural networks with the most powerful supervised learning models. The conclusion is that a small number of even unbalanced data allows to provide models with sufficient performance but more knowledge on the context might improve the results. |
Keywords: | ventriculomegaly machine learning data mining detection fetal medicine |
Document type: | info:eu-repo/semantics/masterThesis |
Issue Date: | Jun-2021 |
Publication license: | http://creativecommons.org/licenses/by-nc-nd/3.0/es/ |
Appears in Collections: | Trabajos finales de carrera, trabajos de investigación, etc. |
Files in This Item:
File | Description | Size | Format | |
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mboschgaTFM0621memòria.pdf | Memòria del TFM | 12,25 MB | Adobe PDF | View/Open |
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