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master's thesis
Normalizacija elektroničkog zdravstvenog kartona
Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing, 2022. urn:nbn:hr:168:474110
Križanec, Matija
University of Zagreb
Faculty of Electrical Engineering and Computing

Institutional repository: FER Repository

Cite this document

Križanec, M. (2022). Normalizacija elektroničkog zdravstvenog kartona (Master's thesis). Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing. Retrieved from https://urn.nsk.hr/urn:nbn:hr:168:474110

Križanec, Matija. "Normalizacija elektroničkog zdravstvenog kartona." Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2022. https://urn.nsk.hr/urn:nbn:hr:168:474110

Križanec, Matija. "Normalizacija elektroničkog zdravstvenog kartona." Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2022. https://urn.nsk.hr/urn:nbn:hr:168:474110

Križanec, M. (2022). 'Normalizacija elektroničkog zdravstvenog kartona', Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, accessed 13 May 2024, https://urn.nsk.hr/urn:nbn:hr:168:474110

Križanec M. Normalizacija elektroničkog zdravstvenog kartona [Master's thesis]. Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing; 2022 [cited 2024 May 13] Available at: https://urn.nsk.hr/urn:nbn:hr:168:474110

M. Križanec, "Normalizacija elektroničkog zdravstvenog kartona", Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, Zagreb, 2022. Available at: https://urn.nsk.hr/urn:nbn:hr:168:474110

Metadata
TitleNormalizacija elektroničkog zdravstvenog kartona
Title (english)Normalization of Electronic Health Record
AuthorMatija Križanec
MentorVlado Sruk (mentor)
Committee memberVlado Sruk (predsjednik povjerenstva)
Committee memberLeonardo Jelenković (član povjerenstva)
Committee memberDejan Škvorc (član povjerenstva)
GranterUniversity of Zagreb
Faculty of Electrical Engineering and Computing
Zagreb
Defense date and country2022-07-07, Croatia
Scientific / art field,
discipline and subdiscipline		TECHNICAL SCIENCES
Computing
Abstract
Mnogi veliki IT projekti u zdravstvu ne uspijevaju ostvariti svoje ciljeve zbog teškog postizanja interoperabilnosti u takvim sustavima. Iz tog razloga razvijeni su mnogi standardi, ali nijedan dovoljno dobro dizajniran kao FHIR. FHIR standard je namijenjen za globalnu upotrebu i u širokom rasponu arhitektura i scenarija. UK Biobank je velika biomedicinska baza podataka, čiji su podaci u nestandardnom i složenom formatu, te je njegova primjena u znanstvenim istraživanjima otežana. U ovom radu je FHIR, kao standard za budućnost interoperabilnosti u zdravstvenim informacijskim sustavima, odabran kao standard za programsku podršku standardizacije UK Biobank skupa podataka. Korišten je smanjeni skup podataka UK Biobank, s značajkama čiji ekvivalenti postoje u dosadašnjim izdanjima FHIR standarda. Normalizirani FHIR podaci mogu se koristiti za lakše treniranje modela strojnog učenja, a potpunom normalizacijom UK Biobank skupa podataka, ta ogromna i jedinstvena količina podataka mogla bi se lakše i jednostavnije koristiti u istraživačke svrhe koje donose veliki doprinos napretku moderne medicine i liječenja te omogućiti više znanstvenih otkrića koja poboljšavaju ljudsko zdravlje.
Abstract (english)
Many large health IT projects fail to achieve their objectives, especially when it comes to interoperability. To tackle this problem, a number of standards have been developed, but none designed as good as FHIR. FHIR standard is intended for global use and in a wide range of architectures and scenarios. UK Biobank is a large biomedical database with data in a non-standard and complex format. As such, its application in scientific research is difficult. In this paper, FHIR, as a standard for future interoperability in health information systems, has been selected as the standard for software standardization of the UK Biobank data set. A reduced set of UK Biobank data was used, containing only features whose equivalents exist in previous editions of the FHIR standard. Normalized FHIR data can be used to train machine learning models more easily. If the UK Biobank data set was normalized in its entirety, this unique amount of data could be used for research purposes that make a major contribution to modern medicine and allow more scientific discoveries that improve human health.
Keywords
Keywords (english)
Languagecroatian
URN:NBNurn:nbn:hr:168:474110
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
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Created on2023-01-13 12:47:13