Zobrazeno 1 - 10
of 28
pro vyhledávání: '"Asan Agibetov"'
Autor:
Christine Wallisch, Asan Agibetov, Daniela Dunkler, Maria Haller, Matthias Samwald, Georg Dorffner, Georg Heinze
Publikováno v:
BMC Medical Research Methodology, Vol 21, Iss 1, Pp 1-12 (2021)
Abstract Background While machine learning (ML) algorithms may predict cardiovascular outcomes more accurately than statistical models, their result is usually not representable by a transparent formula. Hence, it is often unclear how specific values
Externí odkaz:
https://doaj.org/article/fd44f25d547f4647968170b6e258fe2e
Publikováno v:
BMC Bioinformatics, Vol 20, Iss 1, Pp 1-10 (2019)
Abstract Background Neural network based embedding models are receiving significant attention in the field of natural language processing due to their capability to effectively capture semantic information representing words, sentences or even larger
Externí odkaz:
https://doaj.org/article/0ef4aa0349dc48c0a82da38f8c66c1fd
Publikováno v:
BMC Bioinformatics, Vol 19, Iss 1, Pp 1-9 (2018)
Abstract Background Biomedical literature is expanding rapidly, and tools that help locate information of interest are needed. To this end, a multitude of different approaches for classifying sentences in biomedical publications according to their co
Externí odkaz:
https://doaj.org/article/1f6b4939f484429c917eca9fa0cdf125
Autor:
Andrea Beck-Tölly, MD, Michael Eder, MD, Dietrich Beitzke, MD, Farsad Eskandary, MD, PhD, Asan Agibetov, PhD, Katharina Lampichler, MD, Martina Hamböck, MD, PhD, Heinz Regele, MD, Johannes Kläger, MD, Maja Nackenhorst, MD, Georg A. Böhmig, MD
Publikováno v:
Transplantation Direct, Vol 6, Iss 8, p e577 (2020)
Background. Interstitial fibrosis (IF) is the common pathway of chronic kidney injury in various conditions. Magnetic resonance imaging (MRI) may be a promising tool for the noninvasive assessment of IF in renal allografts. Methods. This prospective
Externí odkaz:
https://doaj.org/article/3f3253579a0d4aacaf8ce710b58bb976
Autor:
Asan Agibetov, Ernesto Jiménez-Ruiz, Marta Ondrésik, Alessandro Solimando, Imon Banerjee, Giovanna Guerrini, Chiara E. Catalano, Joaquim M. Oliveira, Giuseppe Patanè, Rui L. Reis, Michela Spagnuolo
Publikováno v:
Journal of Biomedical Semantics, Vol 9, Iss 1, Pp 1-22 (2018)
Abstract Background Pathogenesis of inflammatory diseases can be tracked by studying the causality relationships among the factors contributing to its development. We could, for instance, hypothesize on the connections of the pathogenesis outcomes to
Externí odkaz:
https://doaj.org/article/25266e397bab4bb98a5f5c3e75766a89
Publikováno v:
Journal of Clinical Medicine; Volume 12; Issue 13; Pages: 4434
Background: Inadvertent intraoperative hypothermia is a common complication that affects patient comfort and morbidity. As the development of hypothermia is a complex phenomenon, predicting it using machine learning (ML) algorithms may be superior to
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=multidiscipl::89f5c75dcc8d579659274f8ffbaca158
Autor:
Christian Hengstenberg, Benjamin Seirer, Johannes Kastner, Daniel Dalos, Philip Anner, Diana Bonderman, R Badr-Eslam, Theresa-Marie Dachs, Günther Laufer, Christian Loewe, René Rettl, Christina Binder, Franz Duca, Guenter Stix, Asan Agibetov, Fabian Dusik, Georg Dorffner, Dietrich Beitzke, Lore Schrutka
Publikováno v:
Heart. 108:1137-1147
BackgroundDiagnosis of cardiac amyloidosis (CA) requires advanced imaging techniques. Typical surface ECG patterns have been described, but their diagnostic abilities are limited.ObjectiveThe aim was to perform a thorough electrophysiological charact
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b74fa9b197a29de6792dae531d9f21de
https://doi.org/10.1136/heartjnl-2021-319846
https://doi.org/10.1136/heartjnl-2021-319846
Autor:
Alessa Stria, Asan Agibetov
Publikováno v:
Proceedings of the 1st Workshop on Scarce Data in Artificial Intelligence for Healthcare.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::0de1bc402ee6ff0459be817a804d9c4e
https://doi.org/10.5220/0011531200003523
https://doi.org/10.5220/0011531200003523
Autor:
Asan Agibetov
Publikováno v:
Pattern Recognition. 133:108977
Learning good quality neural graph embeddings has long been achieved by minimizing the point-wise mutual information (PMI) for co-occurring nodes in simulated random walks. This design choice has been mostly popularized by the direct application of t
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::5ff62477e81777b88b7315a2bddd3e93
https://doi.org/10.1016/j.patcog.2022.108977
https://doi.org/10.1016/j.patcog.2022.108977
Autor:
Renate Kain, Asan Agibetov, Diana Bonderman, Franz Duca, Julia Mascherbauer, Matthias Koschutnik, Andreas A. Kammerlander, Hermine Agis, Lore Schrutka, Georg Dorffner, Christian Nitsche, Theresa-Marie Dachs, Christian Hengstenberg, Johannes Kastner, René Rettl, Michaela Auer-Grumbach, Matthias Samwald, Alessa Stria, Carolina Donà, Christina Binder
Publikováno v:
Journal of Personalized Medicine
Journal of Personalized Medicine, Vol 11, Iss 1268, p 1268 (2021)
Journal of Personalized Medicine; Volume 11; Issue 12; Pages: 1268
Journal of Personalized Medicine, Vol 11, Iss 1268, p 1268 (2021)
Journal of Personalized Medicine; Volume 11; Issue 12; Pages: 1268
Aims: We tested the hypothesis that artificial intelligence (AI)-powered algorithms applied to cardiac magnetic resonance (CMR) images could be able to detect the potential patterns of cardiac amyloidosis (CA). Readers in CMR centers with a low volum
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::92ed739d87464bd99e6867588c632200
https://pubmed.ncbi.nlm.nih.gov/34945740
https://pubmed.ncbi.nlm.nih.gov/34945740