Zobrazeno 1 - 10
of 16
pro vyhledávání: '"Matjaz Kukar"'
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
Publikováno v:
Engineering Applications of Artificial Intelligence. 37:194-206
In this paper we propose improved algorithms for the discovery of significant paths and cycles that dynamically evolve through time in a series of multi-level directed graphs. First, we search for the most probable paths and combine them into cluster
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::2f8f1a264d7cc1b4acd2635ea0328a2c
https://doi.org/10.1016/j.engappai.2014.09.012
https://doi.org/10.1016/j.engappai.2014.09.012
Autor:
Petar Vračar, Josip Musić, Miha Drole, Ante Panjkota, Matjaz Kukar, Ivo Stančić, Igor Kononenko
Publikováno v:
ICAT
The problem of detecting objects and their movements in sensor data is of crucial importance in providing safe navigation through both indoor and outdoor environments for the visually impaired. In our setting we use depth- sensor data obtained from a
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::bb1306560fa37a755e21fd9c3dedc442
https://www.bib.irb.hr/784190
https://www.bib.irb.hr/784190
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
Publikováno v:
Lecture Notes in Computer Science ISBN: 9783540748243
IDA
IDA
Estimating the reliability of individual classifications is very important in several applications such as medical diagnosis. Recently, the transductive approach to reliability estimation has been proved to be very efficient when used with several ma
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::8bbfa6d69a7da2d857e620baf220810e
https://doi.org/10.1007/978-3-540-74825-0_4
https://doi.org/10.1007/978-3-540-74825-0_4
Publikováno v:
CBMS
Artificial Intelligence in Medicine ISBN: 9783540627098
AIME
Artificial Intelligence in Medicine ISBN: 9783540627098
AIME
Ischaemic heart disease is one of the world's most important causes of mortality, so improvements and rationalization of diagnostic procedures would be very useful. The four diagnostic levels consist of evaluation of signs and symptoms of the disease
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::528cdfc02ad57444b8152c45e09285dd
https://doi.org/10.1109/cbms.1997.596411
https://doi.org/10.1109/cbms.1997.596411
Publikováno v:
Computers in Cardiology 1997.
The diagnostic process of coronary artery disease (CAD) consists of evaluation of symptoms and signs of the disease and ECG at rest, ECG during exercise, myocardial perfusion scintigraphy (MPS) and coronary angiography. Machine Learning (ML) can use
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::d260d323c541e6eac7bf4aad077bb2d6
https://doi.org/10.1109/cic.1997.647829
https://doi.org/10.1109/cic.1997.647829
Autor:
Matjaz Kukar, Igor Kononenko
Publikováno v:
Lecture Notes in Computer Science ISBN: 9783540440369
ECML
ECML
In the past decades Machine Learning algorithms have been successfully used in numerous classification problems. While they usually significantly outperform domain experts (in terms of classification accuracy or otherwise), they are mostly not being
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::fad01eba5170a507bff76ed224e5b3fd
https://doi.org/10.1007/3-540-36755-1_19
https://doi.org/10.1007/3-540-36755-1_19
Autor:
Matej Pičulin, Tim Smole, Bojan Žunkovič, Enja Kokalj, Marko Robnik-Šikonja, Matjaž Kukar, Dimitrios I Fotiadis, Vasileios C Pezoulas, Nikolaos S Tachos, Fausto Barlocco, Francesco Mazzarotto, Dejana Popović, Lars S Maier, Lazar Velicki, Iacopo Olivotto, Guy A MacGowan, Djordje G Jakovljević, Nenad Filipović, Zoran Bosnić
Publikováno v:
JMIR Medical Informatics, Vol 10, Iss 2, p e30483 (2022)
BackgroundCardiovascular disorders in general are responsible for 30% of deaths worldwide. Among them, hypertrophic cardiomyopathy (HCM) is a genetic cardiac disease that is present in about 1 of 500 young adults and can cause sudden cardiac death (S
Externí odkaz:
https://doaj.org/article/75836ffdc4b849e6802587e4dfe42293
Autor:
Matjaz Kukar
Publikováno v:
Artificial Intelligence in Medicine ISBN: 9783540422945
AIME
AIME
In the past decades Machine Learning tools have been successfully used in several medical diagnostic problems. While they often significantly outperform expert physicians (in terms of diagnostic accuracy, sensitivity, and specificity), they are mostl
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::8763db46d35ecab0210119d2e15cc6dd
https://doi.org/10.1007/3-540-48229-6_12
https://doi.org/10.1007/3-540-48229-6_12