Dubinska analiza podataka iz baze medicinske dokumentacije o pacijentima

undergraduate thesis

• Title (english): Data Mining of Patients Medical Documentation Database
• Author: Petar Borko
• Mentor: Mislav Grgić (mentor)
• Committee member: Mislav Grgić (predsjednik povjerenstva)
• Committee member: Sonja Grgić (član povjerenstva)
• Committee member: Tomislav Kos (član povjerenstva)
• Granter: University of Zagreb; Faculty of Electrical Engineering and Computing; Zagreb
• Defense date and country: 2021-07-01, Croatia
• Scientific / art field, discipline and subdiscipline: TECHNICAL SCIENCES; Computing

Abstract

Čovječanstvu je oduvijek cilj bio predvidjeti budućnost uvidom u informacije dobivene iz sakupljenih podataka. U tu svrhu, kao posljedica razvoja tehnologije za spremanje podataka i integracijom alata strojnog učenja i statistike razvija se dubinska analiza podataka kao grana računarske znanosti koja se bavi pronalaženjem zanimljivih i korisnih uzoraka i veza u podacima. Velike skupove podataka obilježava njihova veličina koja značajno odstupa od prosječne. Dubinska analiza danas se najčešće veže za velike skupove podataka jer omogućuje njihovu obradu i analizu uz pomoć visoke procesorske snage i efikasno implementirane algoritme strojnog učenja. Cilj ovog rada je proučiti mogućnosti dubinske analize korištenjem jednog algoritma strojnog učenja te provođenjem postupka obrade i analize na primjeru medicinske baze podataka.

Abstract (english)

The possibility of predicting the future by collecting information from data has always been one of the main goals of humanity. As such, with further development of storage devices and integration of machine learning and statistics tools, we are reviewing the development of data mining as a branch of computer science which examines finding interesting and useful data patterns, establishing connections between them. In today’s world, data mining is usually connected to big data, main reason being the processing and analyzing possibility using available high hardware capabilities and efficient machine learning implementations. Goal of this thesis is to determine the capabilities of data mining by exploring an example machine learning algorithm and reviewing the data processing and analysis on a medical database.

• Keywords: dubinska analiza podataka; umjetna inteligencija; strojno učenje; statistika; grupiranje; k-means; veliki skupovi podataka; pronalaženje uzoraka; analiza medicinskih podataka
• Keywords (english): data mining; artificial intelligence; machine learning; statistics; clustering; k-means; big data; pattern recognition; medical database analysis
• Language: croatian
• URN:NBN: urn:nbn:hr:168:723576
• Study programme: Title: 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 resource: Text
• File origin: Born digital
• Access conditions: Closed access
• Created on: 2023-01-14 20:08:18