Dec 12, 2019   5:55 p.m. Otília
Academic information system

Summary of topics offered - Faculty of Electrical Engineering and Information Technology


Basic information

Type of work: Diploma thesis
Topic: Vývoj algoritmov strojového učenia pre identifikáciu núdzových stavov v nameraných dátach v telemedicíne
Title of topic in English: 104/5000 Development of machine learning algorithms for identification of emergency states in measured data in telemedicine
State of topic: approved (prof. Dr. Ing. Miloš Oravec - Study programme supervisor)
Thesis supervisor: Ing. Anton Kuzma, PhD.
Faculty: Faculty of Electrical Engineering and Information Technology
Supervising department: Institute of Electronics and Phototonics - FEEIT
Max. no. of students: 1
Academic year:2019/2020
Proposed by: Ing. Anton Kuzma, PhD.
Summary: Telemedicína predstavuje diaľkový prenos nameraných lekárskych dát., ktoré je potrebné vyhodnocovať špecializovaným pracovníkom. V prípade meraní dát z hľadiska prevencie, či prípadného pozorovania zmien signálov mimo periódu hodnotenia špecialistom vzniká priestor na autonómny režim vyhodnocovania dát pomocou algoritmov strojového učenia. Takýmto spôsobom sa zvyšuje prevencia a miera dohľadu nad postupom ochorenia.



Limitations of the topic

To sign up for a topic it is necessary to fulfil one of the following restrictions

Restrictions by study
The table shows restrictions by study to which the student has to be enrolled in order to sign up for the given topic.

ProgrammeTrack
I-API Applied InformaticsI-API-MSUS Modeling and Simulation of Event Systems

Limit to courses
The table shows limitations of a course the student has to complete to be able to register for a given topic.

DepartmentCourse title
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