caa a22 4500 60546829X CHVBK 20210128100316.0 cr unu---uuuuu 210128e20150101xx s 000 0 eng 10.1007/s00500-014-1240-x doi (NATIONALLICENCE)springer-10.1007/s00500-014-1240-x A polynomial based algorithm for detection of embolism [Elektronische Daten] [Adem Karahoca, M. Tunga] The Transcranial Doppler ultrasound can be used to detect asymptomatic circulating cerebral emboli. Emboli indicate particles that can plug the arterial system. Asymptomatic emboli signals help to discover critical stroke events by taking the embolus activities into consideration. Cerebral emboli detection is searched deeply in the literature. But none of them proposed a polynomial method to generalize the solution of the emboli detection. High Dimensional Model Representation (HDMR) philosophy is an effective way of generating an analytical model for a given multivariate data modeling problem, that is, HDMR can be used in constructing a general polynomial model for detecting embolism. In this study, emboli related data set was collected from $$35$$ 35 different patients. HDMR based methods and various data mining techniques were used to detect emboli through that data set. The Euclidean Matrix Based Indexing HDMR method has an important superiority in terms of generating a polynomial model which can then be used in other emboli detection problems without a training process. The method also shows satisfactory results in generalizing the emboli characteristics when compared with the other methods. Springer-Verlag Berlin Heidelberg, 2014 Emboli nationallicence Polynomial based Classification nationallicence Multivariate data partitioning nationallicence Approximation nationallicence HDMR nationallicence Karahoca Adem Software Engineering Department, Faculty of Engineering, Bahçeşehir University, Beşiktaş, 34349, Istanbul, Turkey aut Tunga M. Software Engineering Department, Faculty of Engineering, Bahçeşehir University, Beşiktaş, 34349, Istanbul, Turkey aut Soft Computing Springer Berlin Heidelberg 19/1(2015-01-01), 167-177 1432-7643 19:1<167 2015 19 500 https://doi.org/10.1007/s00500-014-1240-x text/html Onlinezugriff via DOI BK010053 XK010053 XK010000 Metadata rights reserved Springer special CC-BY-NC licence nationallicence 1 research-article jats NATIONALLICENCE NATIONALLICENCE NL-springer NATIONALLICENCE 856 40 https://doi.org/10.1007/s00500-014-1240-x text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Karahoca Adem Software Engineering Department, Faculty of Engineering, Bahçeşehir University, Beşiktaş, 34349, Istanbul, Turkey aut NATIONALLICENCE 700 1- Tunga M. Software Engineering Department, Faculty of Engineering, Bahçeşehir University, Beşiktaş, 34349, Istanbul, Turkey aut NATIONALLICENCE 773 0- Soft Computing Springer Berlin Heidelberg 19/1(2015-01-01), 167-177 1432-7643 19:1<167 2015 19 500