prikaz prve stranice dokumenta Dubinska analiza biomedicinskih vremenskih nizova zasnovana na računalnom radnom okviru za izlučivanje značajki
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doctoral thesis
Dubinska analiza biomedicinskih vremenskih nizova zasnovana na računalnom radnom okviru za izlučivanje značajki
Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing, 2012. urn:nbn:hr:168:228345
Jović, Alan
University of Zagreb
Faculty of Electrical Engineering and Computing
Department of Electronics, Microelectronics, Computer and Intelligent Systems

Institutional repository: FER Repository

Cite this document

Jović, A. (2012). Dubinska analiza biomedicinskih vremenskih nizova zasnovana na računalnom radnom okviru za izlučivanje značajki (Doctoral thesis). Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing. Retrieved from https://urn.nsk.hr/urn:nbn:hr:168:228345

Jović, Alan. "Dubinska analiza biomedicinskih vremenskih nizova zasnovana na računalnom radnom okviru za izlučivanje značajki." Doctoral thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2012. https://urn.nsk.hr/urn:nbn:hr:168:228345

Jović, Alan. "Dubinska analiza biomedicinskih vremenskih nizova zasnovana na računalnom radnom okviru za izlučivanje značajki." Doctoral thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2012. https://urn.nsk.hr/urn:nbn:hr:168:228345

Jović, A. (2012). 'Dubinska analiza biomedicinskih vremenskih nizova zasnovana na računalnom radnom okviru za izlučivanje značajki', Doctoral thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, accessed 03 January 2025, https://urn.nsk.hr/urn:nbn:hr:168:228345

Jović A. Dubinska analiza biomedicinskih vremenskih nizova zasnovana na računalnom radnom okviru za izlučivanje značajki [Doctoral thesis]. Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing; 2012 [cited 2025 January 03] Available at: https://urn.nsk.hr/urn:nbn:hr:168:228345

A. Jović, "Dubinska analiza biomedicinskih vremenskih nizova zasnovana na računalnom radnom okviru za izlučivanje značajki", Doctoral thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, Zagreb, 2012. Available at: https://urn.nsk.hr/urn:nbn:hr:168:228345

Metadata
TitleDubinska analiza biomedicinskih vremenskih nizova zasnovana na računalnom radnom okviru za izlučivanje značajki
Title (english)Data mining of biomedical time-series based on computer framework for feature extraction
AuthorAlan Jović
MentorNikola Bogunović (mentor)
Committee memberSven Lončarić (predsjednik povjerenstva)
Committee memberLeo Budin (član povjerenstva)
Committee memberDragan Gamberger (član povjerenstva)
GranterUniversity of Zagreb
Faculty of Electrical Engineering and Computing
(Department of Electronics, Microelectronics, Computer and Intelligent Systems)
Zagreb
Defense date and country2012-04-20, Croatia
Scientific / art field,
discipline and subdiscipline		TECHNICAL SCIENCES
Computing
Universal decimal classification
(UDC)		004 - Computer science and technology. Computing. Data processing
Abstract
Analiza biomedicinskih vremenskih nizova (BVN) obuhvaća široko interdisciplinarno područje. Istraživači u tom području nastoje kvantizirati složenost biološkog sustava kako bi se ostvarilo lakše razlikovanje između zdravog i bolesnog organizma. Uloga računarstva u tim istraživanjima je izlučivanje i dubinska analiza značajki. Cilj ove disertacije je sistematizirati pristupe izlučivanju značajki i predložiti sveobuhvatan postupak analize podataka na putu od baze podataka do konačnog modela koji ce omogućiti što bolje rezultate pri razvrstavanju poremećaja BVN. U tu svrhu predlaže se implementacija računalnog radnog okvira koji omogućuje izlučivanje velikog broja značajki za pojedinu vrstu BVN. U okviru disertacije implementacija okvira provedena je za područje analize srčanog ritma. Pritom su detaljno opisane vremenske, frekvencijske, vremensko-frekvencijske i nelinearne značajke korištene u tom području. Razvijena su dva nova nelinearna postupka za izlučivanje značajki iz BVN: abecedna entropija i napredna analiza slijednog trenda, za koje se pokazuje da poboljšavaju rezultate razvrstavanja poremećaja. Sustavni postupak vrednovan je na dva zasebna problema razvrstavanja, a postignuta je viša točnost od sličnih pristupa navedenih u literaturi. Rezultati dobiveni ovom disertacijom unaprijeđuju područje računalne analize BVN jer daju radni okvir temeljen na najboljoj praksi za postizanje visoke točnosti razvrstavanja poremećaja.
Abstract (english)
Analysis of biomedical time-series encompasses a broad interdisciplinary area of scientific research. Researchers in this area intend to quantify the complexity of biological system in order to facilitate the differentiation between healthy and unhealthy organisms. The role of computing in this research is mostly related to feature extraction and data mining. The aim of this thesis is to provide a systematic approach starting from databases and continuing through feature extraction, data mining, and model evaluation that would ensure more accurate classification results for biomedical time-series analysis. As a part of the systematic approach, an implementation of a computer framework is proposed that consists of a large number of domain-relevant features. In this thesis, the framework is built for the domain of heart rhythm. The described features include: time domain, frequency domain, time-frequency, and nonlinear measures. Additional two novel methods for feature extraction are also proposed: alphabet entropy and advanced sequential trend analysis, which are shown to increase classification accuracy. The proposed method is evaluated on two distinct classification problems and the obtained results are better than any previously reported in literature. The results of this thesis contribute to the field of computer analysis of biomedical time-series because they provide a framework based on best practice for achieving high discrimination of different types of disorders.
Keywords
Keywords (english)
Languagecroatian
URN:NBNurn:nbn:hr:168:228345
Study programmeTitle: Computer Science
Study programme type: university
Study level: postgraduate
Academic / professional title: Doktor znanosti (Doktor znanosti)
Catalog URLhttp://lib.fer.hr/cgi-bin/koha/opac-detail.pl?biblionumber=38858
Type of resourceText
Extent195 str ; 30 cm
File originBorn digital
Access conditionsClosed access
Terms of useLicence In copyright icon
Created on2019-07-17 08:25:11