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master's thesis
Rani probir za otkrivanje preeklampsije
2019. urn:nbn:hr:168:121825
Rupe, Marina
University of Zagreb
Faculty of Electrical Engineering and Computing

Cite this document

Rupe, M. (2019). Rani probir za otkrivanje preeklampsije (Master's thesis). Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing. Retrieved from https://urn.nsk.hr/urn:nbn:hr:168:121825

Rupe, Marina. "Rani probir za otkrivanje preeklampsije." Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2019. https://urn.nsk.hr/urn:nbn:hr:168:121825

Rupe, Marina. "Rani probir za otkrivanje preeklampsije." Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2019. https://urn.nsk.hr/urn:nbn:hr:168:121825

Rupe, M. (2019). 'Rani probir za otkrivanje preeklampsije', Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, accessed 15 November 2024, https://urn.nsk.hr/urn:nbn:hr:168:121825

Rupe M. Rani probir za otkrivanje preeklampsije [Master's thesis]. Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing; 2019 [cited 2024 November 15] Available at: https://urn.nsk.hr/urn:nbn:hr:168:121825

M. Rupe, "Rani probir za otkrivanje preeklampsije", Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, Zagreb, 2019. Available at: https://urn.nsk.hr/urn:nbn:hr:168:121825

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Metadata
TitleRani probir za otkrivanje preeklampsije
Title (english)Early Screening for Preeclampsia
AuthorMarina Rupe
MentorMile Šikić (mentor)
Committee memberMile Šikić (član povjerenstva)
Committee memberDamir Seršić (član povjerenstva)
Committee memberKrešimir Križanović (član povjerenstva)
GranterUniversity of Zagreb
Faculty of Electrical Engineering and Computing
Zagreb
Defense date and country2019-07-04, Croatia
Scientific / art field,
discipline and subdiscipline		TECHNICAL SCIENCES
Computing
Abstract
Preeklampsija je poremećaj koji zahvaća 2-8% trudnoća i može imati fatalne posljedice za majku i dijete. Ranim probirom za preeklampsiju može se identificirati visokorizične skupine i započeti tretman lijekovima. Najnovija istraživanja pokazuju kako se korištenjem postojećih statističkih metoda i algoritama strojnog učenja može poboljšati procjena rizika za preeklampsiju. Korištenjem modernih metoda, rizik se može procjeniti već u prvom tromjesečju trudnoće. Napravljena je web aplikacija za upravljanje podacima o trudnoćama pacijenata koja omogućuje procjenu rizika za preeklampsiju i generiranje nalaza.
Abstract (english)
Preeclampsia is a disorder which affects 2-8% of pregnancies and can have fatal consequences for both the mother and child. Early screening can identify high-risk groups so that medication can be started. Latest research has shown that using known statistical methods and machine learning algorithms can help with preeclampsia risk estimation. Using modern methods, the risk can be estimated as early as the first trimester of pregnancy. A web application for managing patient pregnancy data has been developed, which enables preeclampsia risk estimation and generating medical reports for that estimation.
Keywords
Keywords (english)
Languageenglish
URN:NBNurn:nbn:hr:168:121825
Study programmeTitle: Computing
Study programme type: university
Study level: graduate
Academic / professional title: magistar/magistra inženjer/inženjerka računarstva (magistar/magistra inženjer/inženjerka računarstva)
Type of resourceText
File originBorn digital
Access conditionsClosed access
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Created on2020-01-07 21:54:18