Zobrazeno 1 - 10
of 1 206
pro vyhledávání: '"P. Atanassova"'
Autor:
I. Stefanov, A. Vodenicharov, P. Atanassova, P. Hrischev, I. Vulkova, D. Stoyanov, N. Tsandev, H. Hristov
Publikováno v:
Bulgarian Journal of Veterinary Medicine, Vol 26, Iss 2, Pp 272-279 (2023)
Detailed mast cell classification is reported in humans and rats, however such classification is not available in porcine common hepatic duct. It is interesting to find out whether mast cells in common hepatic duct are able to produce ghrelin, which
Externí odkaz:
https://doaj.org/article/eafd94353dac4c2c81104eb7ac78ffb2
Publikováno v:
Българска неврология, Vol 24, Iss 2 (2023)
Контраст-индуцираната енцефалопатия (КИЕ) е рядко наблюдавано усложнение на контраст-медиираните ендоваскуларни терапевтични и диагно
Externí odkaz:
https://doaj.org/article/9346f876f6a847dba68e95ebc25f2a9a
Autor:
Eray Halil, B. Atanassova, M. Hristova, K. Chompalov, N. Traikova, N. Atanassova, E. Dzhambazova, P. Atanassova
Publikováno v:
Българска неврология, Vol 24, Iss 1 (2023)
Компютър-томографската пепфузия (КТП) на мозъчния паренхим е достъпен и информативен невроизобразяващ метод, който позволява да се разш
Externí odkaz:
https://doaj.org/article/df8bb9b42bcd413db166c1b610f55391
Publikováno v:
Българска неврология, Vol 22, Iss 2 (2021)
Транскраниалната магнитна стимулация (TМС) е утвърден неврофизиологичен инструмент за изследване целостта на кортикомускулния път при
Externí odkaz:
https://doaj.org/article/22f9a795e8b443a2960164ace6ff0440
Autor:
Gutehrlé, Nicolas, Atanassova, Iana
The digitisation campaigns carried out by libraries and archives in recent years have facilitated access to documents in their collections. However, exploring and exploiting these documents remain difficult tasks due to the sheer quantity of document
Externí odkaz:
http://arxiv.org/abs/2403.19201
Publikováno v:
Българска неврология, Vol 21, Iss 3 (2020)
Цел: Целта на изследването е да се установи влиянието на някои съдови рискови фактори (СРФ) върху когнитивното функциониране при клиничн
Externí odkaz:
https://doaj.org/article/5345b7e0cb1544c997658ed56f534c07
This demo paper presents UnScientify, an interactive system designed to detect scientific uncertainty in scholarly full text. The system utilizes a weakly supervised technique that employs a fine-grained annotation scheme to identify verbally formula
Externí odkaz:
http://arxiv.org/abs/2307.14236
Autor:
Gutehrlé, Nicolas, Atanassova, Iana
Publikováno v:
Journal of Data Mining & Digital Humanities, NLP4DH, Digital humanities in languages (May 30, 2022) jdmdh:9093
Background. In recent years, libraries and archives led important digitisation campaigns that opened the access to vast collections of historical documents. While such documents are often available as XML ALTO documents, they lack information about t
Externí odkaz:
http://arxiv.org/abs/2202.08125
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