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undergraduate thesis
Analiza metagenomskih podataka u svrhu predviđanja dijabetesa
Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing, 2023. urn:nbn:hr:168:211776
Kaštela, Bruna
University of Zagreb
Faculty of Electrical Engineering and Computing

Institutional repository: FER Repository

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Kaštela, B. (2023). Analiza metagenomskih podataka u svrhu predviđanja dijabetesa (Undergraduate thesis). Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing. Retrieved from https://urn.nsk.hr/urn:nbn:hr:168:211776

Kaštela, Bruna. "Analiza metagenomskih podataka u svrhu predviđanja dijabetesa." Undergraduate thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2023. https://urn.nsk.hr/urn:nbn:hr:168:211776

Kaštela, Bruna. "Analiza metagenomskih podataka u svrhu predviđanja dijabetesa." Undergraduate thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2023. https://urn.nsk.hr/urn:nbn:hr:168:211776

Kaštela, B. (2023). 'Analiza metagenomskih podataka u svrhu predviđanja dijabetesa', Undergraduate thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, accessed 26 June 2024, https://urn.nsk.hr/urn:nbn:hr:168:211776

Kaštela B. Analiza metagenomskih podataka u svrhu predviđanja dijabetesa [Undergraduate thesis]. Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing; 2023 [cited 2024 June 26] Available at: https://urn.nsk.hr/urn:nbn:hr:168:211776

B. Kaštela, "Analiza metagenomskih podataka u svrhu predviđanja dijabetesa", Undergraduate thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, Zagreb, 2023. Available at: https://urn.nsk.hr/urn:nbn:hr:168:211776

Metadata
TitleAnaliza metagenomskih podataka u svrhu predviđanja dijabetesa
Title (english)Diabetes prediction using metagenomic datasets
AuthorBruna Kaštela
MentorMirjana Domazet-Lošo (mentor)
Committee memberMirjana Domazet-Lošo (predsjednik povjerenstva)
Committee memberMario Brčić (član povjerenstva)
Committee memberMihael Kovač (član povjerenstva)
GranterUniversity of Zagreb
Faculty of Electrical Engineering and Computing
Zagreb
Defense date and country2023-06-30, Croatia
Scientific / art field,
discipline and subdiscipline		TECHNICAL SCIENCES
Computing
Abstract
Strojno učenje sve je popularniji alat korišten u medicinskoj dijagnostici. U ovom je radu istraženo strojno učenje u svrhu predikcije šećerne bolesti na temelju metagenomskih podataka pacijenata. Modeli su izgrađeni algoritmima slučajne šume, stroja potpornih vektora i ekstremnog pojačivanja gradijentom. Uz to, skupu podataka smanjena je dimenzionalost koristeći različite metode odabira značajki. Kako bi se model bolje prilagodio problemu, napravljena je i verzija algoritma rekurzivne eliminacije za odabir značajki. Dobiveni rezultati su analizirani i vizualizirani te uspoređeni s postojećim rješenjem. Rješenje je predloženo u programskom jeziku Python pomoću biblioteka Scikit-learn i XGBoost.
Abstract (english)
Machine learning is becoming an increasingly popular tool used in medical diagnostics. This study explores machine learning for the purpose of predicting diabetes based on patients’ metagenomic data. Models were built using algorithms such as random forest, support vector machines and extreme gradient boosting. Additionally, the dimensionality of the dataset was reduced using various feature selection methods. To enhance the model’s adaptability to the problem, a custom version of the recursive feature elimination algorithm was additionally implemented. The obtained results were analyzed, visualized and compared to the existing solution. The solution was implemented in the Python programming language using the Scikit-learn and XGBoost libraries.
Keywords
Keywords (english)
Languagecroatian
URN:NBNurn:nbn:hr:168:211776
Study programmeTitle: Computing
Study programme type: university
Study level: undergraduate
Academic / professional title: sveučilišni/a prvostupnik/ prvostupnica (baccalaureus/baccalaurea) inženjer/inženjerka računarstva (sveučilišni/a prvostupnik/ prvostupnica (baccalaureus/baccalaurea) inženjer/inženjerka računarstva)
Type of resourceText
File originBorn digital
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Created on2023-07-13 10:11:22