Zobrazeno 1 - 10
of 697
pro vyhledávání: '"literature based discovery"'
Publikováno v:
BMC Bioinformatics, Vol 25, Iss 1, Pp 1-20 (2024)
Abstract Background Literature-based discovery (LBD) aims to help researchers to identify relations between concepts which are worthy of further investigation by text-mining the biomedical literature. While the LBD literature is rich and the field is
Externí odkaz:
https://doaj.org/article/7bc7adfe58f949c08cc3c887918049af
Autor:
Ilya Tyagin, Ilya Safro
Publikováno v:
BMC Bioinformatics, Vol 25, Iss 1, Pp 1-28 (2024)
Abstract Background Automated hypothesis generation (HG) focuses on uncovering hidden connections within the extensive information that is publicly available. This domain has become increasingly popular, thanks to modern machine learning algorithms.
Externí odkaz:
https://doaj.org/article/489eff1b44b941ed91aa87937ac56c1d
Autor:
Judita Preiss
Publikováno v:
BMC Medical Informatics and Decision Making, Vol 24, Iss S2, Pp 1-8 (2024)
Abstract Background Traditional literature based discovery is based on connecting knowledge pairs extracted from separate publications via a common mid point to derive previously unseen knowledge pairs. To avoid the over generation often associated w
Externí odkaz:
https://doaj.org/article/16a7467b0b634502a582b729cf5c75c2
Autor:
Dan Li, Leihong Wu, Mingfeng Zhang, Svitlana Shpyleva, Ying-Chi Lin, Ho-Yin Huang, Ting Li, Joshua Xu
Publikováno v:
Frontiers in Drug Safety and Regulation, Vol 4 (2024)
Pharmacovigilance plays a crucial role in ensuring the safety of pharmaceutical products. It involves the systematic monitoring of adverse events and the detection of potential safety concerns related to drugs. Manual literature screening for pharmac
Externí odkaz:
https://doaj.org/article/4fb1097fde0a401ebc5def1a72d69c78
Publikováno v:
Big Data and Cognitive Computing, Vol 8, Iss 11, p 146 (2024)
The exponential growth of biomedical literature necessitates advanced methods for Literature-Based Discovery (LBD) to uncover hidden, meaningful relationships and generate novel hypotheses. This research integrates Large Language Models (LLMs), parti
Externí odkaz:
https://doaj.org/article/c228d3fddb274d489eeb2be6a41e197e
Autor:
Robert J. Millikin, Kalpana Raja, John Steill, Cannon Lock, Xuancheng Tu, Ian Ross, Lam C. Tsoi, Finn Kuusisto, Zijian Ni, Miron Livny, Brian Bockelman, James Thomson, Ron Stewart
Publikováno v:
BMC Bioinformatics, Vol 24, Iss 1, Pp 1-14 (2023)
Abstract Background The PubMed archive contains more than 34 million articles; consequently, it is becoming increasingly difficult for a biomedical researcher to keep up-to-date with different knowledge domains. Computationally efficient and interpre
Externí odkaz:
https://doaj.org/article/d8781b15ff3f482f95868b84ad1c6b1a
Akademický článek
Tento výsledek nelze pro nepřihlášené uživatele zobrazit.
K zobrazení výsledku je třeba se přihlásit.
K zobrazení výsledku je třeba se přihlásit.
Autor:
Judita Preiss
Publikováno v:
BMC Bioinformatics, Vol 23, Iss S9, Pp 1-10 (2023)
Abstract Background Automatic literature based discovery attempts to uncover new knowledge by connecting existing facts: information extracted from existing publications in the form of $$A \rightarrow B$$ A → B and $$B \rightarrow C$$ B → C relat
Externí odkaz:
https://doaj.org/article/fa68fdc89c9e4bc98efd49c0567dfefc
Akademický článek
Tento výsledek nelze pro nepřihlášené uživatele zobrazit.
K zobrazení výsledku je třeba se přihlásit.
K zobrazení výsledku je třeba se přihlásit.
Autor:
Yakub Sebastian, Neil R. Smalheiser
Publikováno v:
Frontiers in Research Metrics and Analytics, Vol 8 (2023)
Externí odkaz:
https://doaj.org/article/6adfd0a07bbb45f38b56b5d9f66243a1