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Pregled bibliografske jedinice broj: 1131611

Use of Regressive Artificial Intelligence and Machine Learning Methods in Modelling of COVID-19 Spread (COVIDAi): Project Review

Blagojević, Anđela; Šušteršič, Tijana; Lorencin, Ivan; Filipović, Nenad
Use of Regressive Artificial Intelligence and Machine Learning Methods in Modelling of COVID-19 Spread (COVIDAi): Project Review // International Scientific Student Conference RI-STEM-2021 - proceedings / Lorencin, Ivan ; Baressi Šegota, Sandi ; Car, Zlatan (ur.).
Rijeka, Hrvatska: Studentski zbor Sveučilišta u Rijeci ; Tehnički fakultet, Sveučilište u Rijeci ; Riteh AI and Robotics Group, 2021. str. 1-5 (predavanje, međunarodna recenzija, cjeloviti rad (in extenso), znanstveni)

CROSBI ID: 1131611 Za ispravke kontaktirajte CROSBI podršku putem web obrasca

Naslov
Use of Regressive Artificial Intelligence and Machine Learning Methods in Modelling of COVID-19 Spread (COVIDAi): Project Review

Autori
Blagojević, Anđela ; Šušteršič, Tijana ; Lorencin, Ivan ; Filipović, Nenad

Vrsta, podvrsta i kategorija rada
Radovi u zbornicima skupova, cjeloviti rad (in extenso), znanstveni

Izvornik
International Scientific Student Conference RI-STEM-2021 - proceedings / Lorencin, Ivan ; Baressi Šegota, Sandi ; Car, Zlatan - : Studentski zbor Sveučilišta u Rijeci ; Tehnički fakultet, Sveučilište u Rijeci ; Riteh AI and Robotics Group, 2021, 1-5

ISBN
978-953-8246-22-7

Skup
International Student Scientific Conference (Ri-STEM 2021)

Mjesto i datum
Rijeka, Hrvatska, 10.06.2021. - 11.06.2021

Vrsta sudjelovanja
Predavanje

Vrsta recenzije
Međunarodna recenzija

Ključne riječi
artificial intelligence ; COVID-19 ; epidemiological models ; machine learning ; personalized models

Sažetak
In this paper, a review of the project Use of Regressive Artificial Intelligence and Machine Learning Methods in Modelling of COVID-19 Spread (COVIDAi) is presented. The main goal of the project is to design two main AI-based models: epidemiological and personalized. After the introduction, a brief description of project partners and activities is provided. Furthermore, a brief description of the two main project activities is provided. After the description of the aforementioned project activities, a review of scientific papers published during project execution is presented.

Izvorni jezik
Engleski

Znanstvena područja
Elektrotehnika, Računarstvo, Temeljne tehničke znanosti, Kliničke medicinske znanosti



POVEZANOST RADA

Projekti:
Ostalo-CEI - 305.6019-20 - Use of regressive artificial intelligence (AI) and machine learning (ML) methods in modelling of COVID-19 spread (COVIDAi) (Car, Zlatan, Ostalo - CEI Extraordinary Call for Proposals 2020) ( CroRIS)
--KK.01.1.1.01.009 - Napredne metode i tehnologije u znanosti o podatcima i kooperativnim sustavima (DATACROSS) (Šmuc, Tomislav; Lončarić, Sven; Petrović, Ivan; Jokić, Andrej; Palunko, Ivana) ( CroRIS)
EK-EFRR-KK.01.1.1.02.0023 - Razvojno-edukacijski centar za metalsku industriju – Metalska jezgra Čakovec (Car, Zlatan, EK - KK.01.1.1.02) ( CroRIS)
--KK.01.2.2.03.0004 - Centar kompetencija za pametne gradove (CEKOM) (Car, Zlatan; Slavić, Nataša; Vilke, Siniša) ( CroRIS)
NadSve-Sveučilište u Rijeci-uniri-tehnic-18-275-1447 - Razvoj inteligentnog ekspertnog sustava za online diagnostiku raka mokračnog mjehura (Car, Zlatan, NadSve - UNIRI potpore) ( CroRIS)

Ustanove:
Tehnički fakultet, Rijeka

Profili:

Avatar Url Ivan Lorencin (autor)

Poveznice na cjeloviti tekst rada:

Pristup cjelovitom tekstu rada sites.google.com

Citiraj ovu publikaciju:

Blagojević, Anđela; Šušteršič, Tijana; Lorencin, Ivan; Filipović, Nenad
Use of Regressive Artificial Intelligence and Machine Learning Methods in Modelling of COVID-19 Spread (COVIDAi): Project Review // International Scientific Student Conference RI-STEM-2021 - proceedings / Lorencin, Ivan ; Baressi Šegota, Sandi ; Car, Zlatan (ur.).
Rijeka, Hrvatska: Studentski zbor Sveučilišta u Rijeci ; Tehnički fakultet, Sveučilište u Rijeci ; Riteh AI and Robotics Group, 2021. str. 1-5 (predavanje, međunarodna recenzija, cjeloviti rad (in extenso), znanstveni)
Blagojević, A., Šušteršič, T., Lorencin, I. & Filipović, N. (2021) Use of Regressive Artificial Intelligence and Machine Learning Methods in Modelling of COVID-19 Spread (COVIDAi): Project Review. U: Lorencin, I., Baressi Šegota, S. & Car, Z. (ur.)International Scientific Student Conference RI-STEM-2021 - proceedings.
@article{article, author = {Blagojevi\'{c}, An\djela and \v{S}u\v{s}ter\v{s}i\v{c}, Tijana and Lorencin, Ivan and Filipovi\'{c}, Nenad}, year = {2021}, pages = {1-5}, keywords = {artificial intelligence, COVID-19, epidemiological models, machine learning, personalized models}, isbn = {978-953-8246-22-7}, title = {Use of Regressive Artificial Intelligence and Machine Learning Methods in Modelling of COVID-19 Spread (COVIDAi): Project Review}, keyword = {artificial intelligence, COVID-19, epidemiological models, machine learning, personalized models}, publisher = {Studentski zbor Sveu\v{c}ili\v{s}ta u Rijeci ; Tehni\v{c}ki fakultet, Sveu\v{c}ili\v{s}te u Rijeci ; Riteh AI and Robotics Group}, publisherplace = {Rijeka, Hrvatska} }
@article{article, author = {Blagojevi\'{c}, An\djela and \v{S}u\v{s}ter\v{s}i\v{c}, Tijana and Lorencin, Ivan and Filipovi\'{c}, Nenad}, year = {2021}, pages = {1-5}, keywords = {artificial intelligence, COVID-19, epidemiological models, machine learning, personalized models}, isbn = {978-953-8246-22-7}, title = {Use of Regressive Artificial Intelligence and Machine Learning Methods in Modelling of COVID-19 Spread (COVIDAi): Project Review}, keyword = {artificial intelligence, COVID-19, epidemiological models, machine learning, personalized models}, publisher = {Studentski zbor Sveu\v{c}ili\v{s}ta u Rijeci ; Tehni\v{c}ki fakultet, Sveu\v{c}ili\v{s}te u Rijeci ; Riteh AI and Robotics Group}, publisherplace = {Rijeka, Hrvatska} }

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