Zobrazeno 1 - 10
of 1 293
pro vyhledávání: '"Biomedical text mining"'
Autor:
Ai-Ru Hsieh, Chen-Yu Tsai
Publikováno v:
European Journal of Medical Research, Vol 29, Iss 1, Pp 1-11 (2024)
Abstract The supervised machine learning method is often used for biomedical relationship extraction. The disadvantage is that it requires much time and money to manually establish an annotated dataset. Based on distant supervision, the knowledge bas
Externí odkaz:
https://doaj.org/article/7d7a954fcc9048b6b569a56acaba2769
Autor:
Negin Sadat Babaiha, Sathvik Guru Rao, Jürgen Klein, Bruce Schultz, Marc Jacobs, Martin Hofmann-Apitius
Publikováno v:
Artificial Intelligence in the Life Sciences, Vol 5, Iss , Pp 100095- (2024)
Biomedical knowledge graphs (KGs) hold valuable information regarding biomedical entities such as genes, diseases, biological processes, and drugs. KGs have been successfully employed in challenging biomedical areas such as the identification of path
Externí odkaz:
https://doaj.org/article/4489f8b37fe44dfb9f4bfce62c3927f1
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
Autor:
Negin Sadat Babaiha, Hassan Elsayed, Bide Zhang, Abish Kaladharan, Priya Sethumadhavan, Bruce Schultz, Jürgen Klein, Bruno Freudensprung, Vanessa Lage-Rupprecht, Alpha Tom Kodamullil, Marc Jacobs, Stefan Geissler, Sumit Madan, Martin Hofmann-Apitius
Publikováno v:
Artificial Intelligence in the Life Sciences, Vol 4, Iss , Pp 100078- (2023)
Background: Biomedical knowledge graphs (KG) have become crucial for describing biological findings in a structured manner. To keep up with the constantly changing flow of knowledge, their embedded information must be regularly updated with the lates
Externí odkaz:
https://doaj.org/article/2d81908cce8d47bdbbb0de9dfedccef6
Publikováno v:
International Journal of Molecular Sciences, Vol 25, Iss 8, p 4503 (2024)
Diabetic kidney disease (DKD) is the leading cause of end-stage renal disease worldwide. This study’s goal was to identify the signaling drivers and pathways that modulate glomerular endothelial dysfunction in DKD via artificial intelligence-enable
Externí odkaz:
https://doaj.org/article/4499537ea580425d8660aa8edf6d6b6a
Publikováno v:
Frontiers in Genetics, Vol 14 (2023)
Syndrome differentiation and treatment is the basic principle of traditional Chinese medicine (TCM) to recognize and treat diseases. Accurate syndrome differentiation can provide a reliable basis for treatment, therefore, establishing a scientific in
Externí odkaz:
https://doaj.org/article/507b5c5fe4e847e7bae1a820a8594325
Autor:
Zhiyu Zhang, Arbee L. P. Chen
Publikováno v:
BMC Bioinformatics, Vol 23, Iss 1, Pp 1-21 (2022)
Abstract Background Biomedical named entity recognition (BioNER) is a basic and important task for biomedical text mining with the purpose of automatically recognizing and classifying biomedical entities. The performance of BioNER systems directly im
Externí odkaz:
https://doaj.org/article/b200eebb3bed4daa9de4c353d449f46c
Akademický článek
Tento výsledek nelze pro nepřihlášené uživatele zobrazit.
K zobrazení výsledku je třeba se přihlásit.
K zobrazení výsledku je třeba se přihlásit.
Akademický článek
Tento výsledek nelze pro nepřihlášené uživatele zobrazit.
K zobrazení výsledku je třeba se přihlásit.
K zobrazení výsledku je třeba se přihlásit.
Publikováno v:
BMC Bioinformatics, Vol 23, Iss 1, Pp 1-13 (2022)
Abstract Background Drug-target interactions (DTIs) are critical for drug repurposing and elucidation of drug mechanisms, and are manually curated by large databases, such as ChEMBL, BindingDB, DrugBank and DrugTargetCommons. However, the number of c
Externí odkaz:
https://doaj.org/article/98b3aa6968ba4cd8a924da4cd87352a2