Zobrazeno 1 - 10
of 1 848
pro vyhledávání: '"Biomedical text"'
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:
Mahira Kirmani, Gagandeep Kour, Mudasir Mohd, Nasrullah Sheikh, Dawood Ashraf Khan, Zahid Maqbool, Mohsin Altaf Wani, Abid Hussain Wani
Publikováno v:
BMC Bioinformatics, Vol 25, Iss 1, Pp 1-21 (2024)
Abstract Background Text summarization is a challenging problem in Natural Language Processing, which involves condensing the content of textual documents without losing their overall meaning and information content, In the domain of bio-medical rese
Externí odkaz:
https://doaj.org/article/239bc44b2e5f46bfa0ff076ca35dad51
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
Publikováno v:
Data in Brief, Vol 51, Iss , Pp 109720- (2023)
The COVID-19 pandemic has underlined the need for reliable information for clinical decision-making and public health policies. As such, evidence-based medicine (EBM) is essential in identifying and evaluating scientific documents pertinent to novel
Externí odkaz:
https://doaj.org/article/c7ba1226d9744eefb5a95b407eead80a
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:
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
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