Summary: A novel approach for accurate prediction of
spontaneous passage of ureteral stones: Support
vector machines
F Dal Moro1,3
, A Abate2,3
, GRG Lanckriet2,3
, G Arandjelovic1
, P Gasparella1
, P Bassi1
, M Mancini1
and F Pagano1
1
Department of Urology, University of Padova, Padova, Italy and 2
Electrical Engineering and Computer Sciences Department, University
of California at Berkeley, Berkeley, California, USA
The objective of this study was to optimally predict the
spontaneous passage of ureteral stones in patients with renal
colic by applying for the first time support vector machines
(SVM), an instance of kernel methods, for classification. After
reviewing the results found in the literature, we compared

Source: Abate, Alessandro - Faculty of Mechanical, Maritime and Materials Engineering, Technische Universiteit Delft

Collections: Engineering