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Paper Details

A comparison of word embeddings for the biomedical natural language processing.
J Biomed Inform
114
2018
human, pre
Adolescent, Adult, Aged, Electronic Health Records, Family Health, Female, Humans, Information Storage and Retrieval, Linguistics, Machine Learning, Male, Medical Informatics, Middle Aged, Minnesota, Models, Statistical, Natural Language Processing, Probability, PubMed, Semantics, Unified Medical Language System, Young Adult
Author NameAffiliation
Yanshan WangMayo Clinic
Sijia LiuMayo Clinic
Naveed AfzalMayo Clinic
Majid Rastegar-MojaradMayo Clinic
Liwei WangMayo Clinic
Feichen ShenMayo Clinic
Paul KingsburyMayo Clinic
Hongfang LiuMayo Clinic
Hongfang LiuMayo Clinic
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Datasets

Dataset
Description
Source Link
PubMedCitations and abstracts of biomedical literatureLink
PubMedCitations and abstracts of biomedical literatureLink
PubMedCitations and abstracts of biomedical literatureLink
PubMedCitations and abstracts of biomedical literatureLink
PubMedCitations and abstracts of biomedical literatureLink
PubMedCitations and abstracts of biomedical literatureLink
PubMedCitations and abstracts of biomedical literatureLink
PubMedCitations and abstracts of biomedical literatureLink
PubMedCitations and abstracts of biomedical literatureLink
PubMedCitations and abstracts of biomedical literatureLink
PubMedCitations and abstracts of biomedical literatureLink
PubMedCitations and abstracts of biomedical literatureLink
PubMedCitations and abstracts of biomedical literatureLink
PubMedCitations and abstracts of biomedical literatureLink
PubMedCitations and abstracts of biomedical literatureLink
Release 1.2