Fernando Sereno

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Foetal weight estimation is a clinically relevant task for proper medical care in perinatal situations. Usually this estimation is based on features such as measurements derived from echographic examinations. Several formulas have been developed by other authors for performing this estimation with limited degree of success. Our approach is based on(More)
Several authors have theoretically determined distribution-free bounds on sample complexity. Formulas based on several learning paradigms have been presented. However, little is known on how these formulas perform and compare with each other in practice. To our knowledge, controlled experimental results using these formulas, and comparing of their behavior,(More)
Foetal weight prediction based on echographic features is an important procedure in perinatal medicine. Classical methods of foetal weight prediction have serious shortcomings in current clinical practice. We investigated the application of Radial Basis Functions (RBF) and Support Vectors Machines (SVM) neural networks in order to predict foetal weights in(More)
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