Učni načrt predmeta

Predmet:
Zdravstveni ekspertni sistemi na daljavo
Course:
Expert Systems for eHealth
Študijski program in stopnja /
Study programme and level		 Študijska smer /
Study field		 Letnik /
Academic year		 Semester /
Semester
Informacijske in komunikacijske tehnologije, 3. stopnja Računalniške strukture in sistemi 1 1
Information and Communication Technologies, 3rd cycle Computer Structures and Systems 1 1
Vrsta predmeta / Course type
Izbirni / Elective
Univerzitetna koda predmeta / University course code:
IKT3-909
Predavanja
Lectures		 Seminar
Seminar		 Vaje
Tutorial		 Klinične vaje
work		 Druge oblike
študija		 Samost. delo
Individ. work		 ECTS
15 15 15 105 5

*Navedena porazdelitev ur velja, če je vpisanih vsaj 15 študentov. Drugače se obseg izvedbe kontaktnih ur sorazmerno zmanjša in prenese v samostojno delo. / This distribution of hours is valid if at least 15 students are enrolled. Otherwise the contact hours are linearly reduced and transfered to individual work.

Nosilec predmeta / Course leader:
izr. prof. dr. Barbara Koroušič Seljak
Sodelavci / Lecturers:
Jeziki / Languages:
Predavanja / Lectures:
Slovenščina, angleščina / Slovenian, English
Vaje / Tutorial:
Pogoji za vključitev v delo oz. za opravljanje študijskih obveznosti:
Prerequisits:
Vsebina:
Content (Syllabus outline):
Temeljna literatura in viri / Readings:
Cilji in kompetence:
Objectives and competences:
Predvideni študijski rezultati:
Intendeded learning outcomes:
Metode poučevanja in učenja:
Learning and teaching methods:
Načini ocenjevanja:
Delež v % / Weight in %
Assesment:
Seminarska naloga
50
Seminar work
Ustni zagovor seminarske naloge
50
Oral defense of seminar work
Reference nosilca / Lecturer's references:
1. B. Koroušić Seljak, V Stibilj, L Pograjc, N Fidler Mis, E Benedik. Food composition databases for effective quality nutritional care. Food chemistry 140 (3), 553-561, 2013
2. T. Eftimov, G. Popovski, M. Petković, B. Koroušić Seljak, D. Kocev. COVID-19 pandemic changes the food consumption patterns. Trends in food science & technology, 2020, vol. 104, str. 268-272. ISSN 0924-2244. DOI: 10.1016/j.tifs.2020.08.017.
3. N. Reščič, T. Eftimov, B. Koroušić Seljak, M. Luštrek. Optimising an FFQ Using a Machine Learning Pipeline to teach an Efficient Nutrient Intake Predictive Model. Nutrients 12(12), 3789, 2020
4. G. Ispirova, T. Eftimov, B. Koroušić Seljak. Evaluating missing value imputation methods for food composition databases. Food and Chemical Toxicology, 111368, 2020
5. S. Mezgec, T. Eftimov, T. Bucher, B. Koroušić Seljak. Mixed deep learning and natural language processing method for fake-food image recognition and standardization to help automated dietary assessment. Public health nutrition 22(7) 1193-1202, 2019