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master's thesis
Modeliranje kliničkog odlučivanja primjenom strojnog učenja
2022. urn:nbn:hr:168:852998
Stanušić, Magdalena
University of Zagreb
Faculty of Electrical Engineering and Computing

Cite this document

Stanušić, M. (2022). Modeliranje kliničkog odlučivanja primjenom strojnog učenja (Master's thesis). Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing. Retrieved from https://urn.nsk.hr/urn:nbn:hr:168:852998

Stanušić, Magdalena. "Modeliranje kliničkog odlučivanja primjenom strojnog učenja." Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2022. https://urn.nsk.hr/urn:nbn:hr:168:852998

Stanušić, Magdalena. "Modeliranje kliničkog odlučivanja primjenom strojnog učenja." Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2022. https://urn.nsk.hr/urn:nbn:hr:168:852998

Stanušić, M. (2022). 'Modeliranje kliničkog odlučivanja primjenom strojnog učenja', Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, accessed 05 December 2024, https://urn.nsk.hr/urn:nbn:hr:168:852998

Stanušić M. Modeliranje kliničkog odlučivanja primjenom strojnog učenja [Master's thesis]. Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing; 2022 [cited 2024 December 05] Available at: https://urn.nsk.hr/urn:nbn:hr:168:852998

M. Stanušić, "Modeliranje kliničkog odlučivanja primjenom strojnog učenja", Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, Zagreb, 2022. Available at: https://urn.nsk.hr/urn:nbn:hr:168:852998

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Metadata
TitleModeliranje kliničkog odlučivanja primjenom strojnog učenja
Title (english)Modeling clinical decision making using machine learning
AuthorMagdalena Stanušić
MentorPetar Mostarac (mentor)
Committee memberPetar Mostarac (predsjednik povjerenstva)
Committee memberHrvoje Hegeduš (član povjerenstva)
Committee memberAlan Šala (član povjerenstva)
GranterUniversity of Zagreb
Faculty of Electrical Engineering and Computing
Zagreb
Defense date and country2022-07-01, Croatia
Scientific / art field,
discipline and subdiscipline		TECHNICAL SCIENCES
Computing
Abstract
Vidjeli smo povijesni razvoj i mnoge algoritme strojnog učenja, njihovu implementaciju te na koji način se sprječava njihova prenaučenost. Također je opisano na koji način su nastale umjetne neuronske mreže, kako ih projektirati i implementirati te na posljetku istrenirati i testirati. U sklopu rada implementirani su navedi algoritmi koji se mogu primijeniti na problem klasifikacije te je projektirana umjetna neuronska mreža.
Abstract (english)
We have seen the historical development and many algorithms of machine learning, their implementation and how to prevent overfitting of those algorithms. It is also described how artificial neural networks were created, how to design and implement them, and ultimately train and test them. As part of the paper, the listed algorithms that can be applied to the classification problem were implemented and an artificial neural network was designed.
Keywords
Keywords (english)
Languagecroatian
URN:NBNurn:nbn:hr:168:852998
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
Terms of useLicence In copyright icon
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Created on2023-01-15 11:15:50