[PubMed].
By Yvonne Perathoner, Koordinatorin Gesundheitsberufe. 2020
685 citations recorded by the source corpus.
U.S. National Library of Medicine National Institutes of Health Search: ( ("Endoscopy, Gastrointestinal"[Mesh] OR ("Endoscopy, Gastrointestinal/contraindications"[Mesh] OR "Endoscopy, Gastrointestinal/methods"[Mesh] OR "Endoscopy, Gastrointestinal/mortality"[Mesh] OR "Endoscopy, Gastrointestinal/standards"[Mesh] OR "Endoscopy, Gastrointestinal/statistics and numerical data"[Mesh] OR "Endoscopy, Gastrointestinal/trends"[Mesh] OR "Endoscopy, Gastrointestinal/utilization"[Mesh]) AND ("last 60 days"[EDat] AND "last 60 days"[PDat])) AND "2010/01/16 15.00"[MHDA]:"2010/01/23 15.00"[MHDA])
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
- Rohan Gupta
- Devesh Srivastava
- Mehar Sahu
- S. Tiwari
- R. K. Ambasta
- Pravir Kumar
- Shiva Maleki Varnosfaderani
Citations in the corpus
- Replay in Deep Learning: Current Approaches and Missing Biological Elements (2021, neutral): “…Aljundi, Lin, Goujaud, & Bengio, 2019; He, Mao, Shao, & Zhu, 2020; Zhao, Xiao, Gan, Zhang, & Xia, 2020; Kurle, Cseke, Klushyn, van der Smagt, & Günnemann, 2020; Chrysakis & Moens, 2020; Kim, Jeong, & Kim, 2020; Tao, Chang, Hong, Wei, & Gong, 2020; Douil-lard, Cord, Ollion, Robert, & Valle, 2020).”
- From cancer patient to cancer survivor : lost in transition (2006, unknown): “NLM. 2005.”
- Artificial intelligence to deep learning: machine intelligence approach for drug discovery (2021, background): “Moreover, sometimes even published literature can be used for target identification, and PubMed (https:// pubmed. ncbi. nlm. nih. gov/) [52] is a major repository of the various published biomedical literature, whose data mining can help in identifying targets for different disorders.”
- Towards Domain Specification of Embedding Models in Medicine (2025, unknown): “We begin with PubMed [31], a comprehensive catalogue of biomedical abstracts, and its full-text counterpart PubMed Central (PMC) [32], anchoring our collection in rigorously vetted scientific discourse.”