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master's thesis
Web aplikacija za procjenu rizika obolijevanja i praćenje tijeka kardiovaskularnih bolesti zasnovana na postupcima nadziranog strojnog učenja
Osijek: Josip Juraj Strossmayer University of Osijek, Faculty of Electrical Engineering, Computer Science and Information Technology Osijek, 2024. urn:nbn:hr:200:720527
Šabanović, Dina
Josip Juraj Strossmayer University of Osijek
Faculty of Electrical Engineering, Computer Science and Information Technology Osijek
Department of Software Engineering
Chair of Programming Languages and Systems

Cite this document

Šabanović, D. (2024). Web aplikacija za procjenu rizika obolijevanja i praćenje tijeka kardiovaskularnih bolesti zasnovana na postupcima nadziranog strojnog učenja (Master's thesis). Osijek: Josip Juraj Strossmayer University of Osijek, Faculty of Electrical Engineering, Computer Science and Information Technology Osijek. Retrieved from https://urn.nsk.hr/urn:nbn:hr:200:720527

Šabanović, Dina. "Web aplikacija za procjenu rizika obolijevanja i praćenje tijeka kardiovaskularnih bolesti zasnovana na postupcima nadziranog strojnog učenja." Master's thesis, Josip Juraj Strossmayer University of Osijek, Faculty of Electrical Engineering, Computer Science and Information Technology Osijek, 2024. https://urn.nsk.hr/urn:nbn:hr:200:720527

Šabanović, Dina. "Web aplikacija za procjenu rizika obolijevanja i praćenje tijeka kardiovaskularnih bolesti zasnovana na postupcima nadziranog strojnog učenja." Master's thesis, Josip Juraj Strossmayer University of Osijek, Faculty of Electrical Engineering, Computer Science and Information Technology Osijek, 2024. https://urn.nsk.hr/urn:nbn:hr:200:720527

Šabanović, D. (2024). 'Web aplikacija za procjenu rizika obolijevanja i praćenje tijeka kardiovaskularnih bolesti zasnovana na postupcima nadziranog strojnog učenja', Master's thesis, Josip Juraj Strossmayer University of Osijek, Faculty of Electrical Engineering, Computer Science and Information Technology Osijek, accessed 17 March 2025, https://urn.nsk.hr/urn:nbn:hr:200:720527

Šabanović D. Web aplikacija za procjenu rizika obolijevanja i praćenje tijeka kardiovaskularnih bolesti zasnovana na postupcima nadziranog strojnog učenja [Master's thesis]. Osijek: Josip Juraj Strossmayer University of Osijek, Faculty of Electrical Engineering, Computer Science and Information Technology Osijek; 2024 [cited 2025 March 17] Available at: https://urn.nsk.hr/urn:nbn:hr:200:720527

D. Šabanović, "Web aplikacija za procjenu rizika obolijevanja i praćenje tijeka kardiovaskularnih bolesti zasnovana na postupcima nadziranog strojnog učenja", Master's thesis, Josip Juraj Strossmayer University of Osijek, Faculty of Electrical Engineering, Computer Science and Information Technology Osijek, Osijek, 2024. Available at: https://urn.nsk.hr/urn:nbn:hr:200:720527

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Metadata
TitleWeb aplikacija za procjenu rizika obolijevanja i praćenje tijeka kardiovaskularnih bolesti zasnovana na postupcima nadziranog strojnog učenja
Title (english)A web application for cardiovacular disease risk assessment and disease course monitoring based on supervised machine learning methods
AuthorDina Šabanović
MentorGoran Martinović (mentor)
Committee memberGoran Martinović (predsjednik povjerenstva)
Committee memberMirko Köhler (član povjerenstva)
Committee memberIvica Lukić (član povjerenstva)
GranterJosip Juraj Strossmayer University of Osijek
Faculty of Electrical Engineering, Computer Science and Information Technology Osijek
(Department of Software Engineering)
(Chair of Programming Languages and Systems)
Osijek
Defense date and country2024-09-26, Croatia
Scientific / art field,
discipline and subdiscipline		TECHNICAL SCIENCES
Computing
Program Engineering
Abstract
sažetak (hrvatski): Glavni cilj ovog diplomskog rada bio je razvoj web aplikacije koja procjenjuje rizik od obolijevanja od kardiovaskularnih bolesti koristeći metode nadziranog strojnog učenja. Aplikacija je implementirana uz pomoću programskih jezika i tehnologija kao što su Python, Django i HTML. U središtu aplikacije nalazi se model temeljen na algoritmu slučajne šume, koji je nakon usporedbe sa stablom odlučivanja, metodom strojeva potpornih vektora i algoritmom k najbližih susjeda... More pokazao najbolje rezultate. Osim što omogućuje pacijentima procjenu svog rizika obolijevanja od kardiovaskularnih bolesti, aplikacija također pruža liječnicima mogućnost stvaranja preporuka temeljenih na zdravstvenom stanju pacijenata. Praćenje tijeka bolesti i praćenje zdravstvenih podataka omogućeno je zahvaljujući sustavu za pohranu. Uz to što pomaže u ranom prepoznavanju rizika, aplikacija omogućuje kontinuirani nadzor i prilagodbu liječenja prema promjenama u zdravstvenom stanju korisnika. Provjera ispravnosti aplikacije obavljena je kroz tri testna slučaja i pokazuje da aplikacija radi ispravno. Less
Abstract (english)
abstract: The main goal of this thesis was to develop a web application that assesses the risk of cardiovascular disease using supervised machine learning methods. The application was implemented using programming languages and technologies Python, Django, and HTML. At the core of the application is a machine learning model based on the random forest algorithm, which, after comparison with decision trees, support vector machines, and the k-nearest neighbors algorithm, had the best ... More results. In addition to allowing patients to assess their risk of developing cardiovascular disease, the application also provides doctors with the ability to create recommendations based on the health status of patients. Disease course monitoring and health data tracking are enabled by a storage system. Besides helping in the early detection of risk, the application allows for continuous monitoring and adjustment of treatment according to changes in the user's health status. The application’s validation was carried out through three test cases and shows that the application functions correctly. Less
Keywords
Keywords (english)
Languagecroatian
URN:NBNurn:nbn:hr:200:720527
Study programmeTitle: Graduate University Study Programme in Computer Engineering
Study programme type: university
Study level: graduate
Academic / professional title: sveučilišni/a magistar/magistra inženjer/inženjerka računarstva (sveučilišni/a magistar/magistra inženjer/inženjerka računarstva)
Type of resourceText
File originBorn digital
Access conditionsOpen access
Terms of useLicence In copyright icon
RepositoryFaculty of Electrical Engineering, Computer Science and Information Technology Osijek
Created on2024-10-18 10:01:44
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