Zobrazeno 1 - 5
of 5
pro vyhledávání: '"Sašo Moškon"'
Autor:
Gregor Gunčar, Matjaž Kukar, Tim Smole, Sašo Moškon, Tomaž Vovko, Simon Podnar, Peter Černelč, Miran Brvar, Mateja Notar, Manca Köster, Marjeta Tušek Jelenc, Žiga Osterc, Marko Notar
Publikováno v:
Heliyon, Vol 10, Iss 8, Pp e29372- (2024)
The growing threat of antibiotic resistance necessitates accurate differentiation between bacterial and viral infections for proper antibiotic administration. In this study, a Virus vs. Bacteria machine learning model was developed to distinguish bet
Externí odkaz:
https://doaj.org/article/45d0ce9391574ac288911225263d43d4
Autor:
Matjaž Kukar, Gregor Gunčar, Tomaž Vovko, Simon Podnar, Peter Černelč, Miran Brvar, Mateja Zalaznik, Mateja Notar, Sašo Moškon, Marko Notar
Publikováno v:
Scientific Reports, Vol 11, Iss 1, Pp 1-9 (2021)
Abstract Physicians taking care of patients with COVID-19 have described different changes in routine blood parameters. However, these changes hinder them from performing COVID-19 diagnoses. We constructed a machine learning model for COVID-19 diagno
Externí odkaz:
https://doaj.org/article/5e6c746d9f7d42ca988860072ce91764
Autor:
Gregor Gunčar, Matjaž Kukar, Tim Smole, Sašo Moškon, Tomaž Vovko, Simon Podnar, Peter Černelč, Miran Brvar, Mateja Notar, Manca Köster, Marjeta Tušek Jelenc, Žiga Osterc, Marko Notar
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::095e2ff498ae3533775c9c6a61d7c883
https://doi.org/10.2139/ssrn.4459567
https://doi.org/10.2139/ssrn.4459567
Autor:
Simon Podnar, Mateja Zalaznik, Mateja Notar, Marko Notar, Gregor Gunčar, Sašo Moškon, Miran Brvar, Matjaž Kukar, Tomaž D. Vovko, Peter Černelč
Publikováno v:
Scientific Reports
Scientific Reports, Vol 11, Iss 1, Pp 1-9 (2021)
Scientific Reports, Vol 11, Iss 1, Pp 1-9 (2021)
Physicians taking care of patients with coronavirus disease (COVID-19) have described different changes in routine blood parameters. However, these changes, hinder them from performing COVID-19 diagnosis. We constructed a machine learning predictive
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::36f37ec5c1a41b9531b1f4feefaa4934
http://arxiv.org/abs/2006.03476
http://arxiv.org/abs/2006.03476
Publikováno v:
Geografski vestnik
Prispevek obravnava metodologijo zbiranja akusticnih podatkov o morskem dnu in njihovo uporabo za kartiranje morskih travnikov. Metoda omogoca hitro in ucinkovito kartiranje velikih obmocij morskih travnikov in zagotavlja zvezno pokritost na celotnem