194 related articles for article (PubMed ID: 35488252)
21. Siamese KG-LSTM: A deep learning model for enriching UMLS Metathesaurus synonymy.
Tran TTT; Nghiem SV; Le VT; Quan TT; Nguyen V; Yip HY; Bodenreider O
Int Conf Knowl Syst Eng; 2020 Nov; 2020():281-286. PubMed ID: 36277606
[TBL] [Abstract][Full Text] [Related]
22. Word embeddings trained on published case reports are lightweight, effective for clinical tasks, and free of protected health information.
Flamholz ZN; Crane-Droesch A; Ungar LH; Weissman GE
J Biomed Inform; 2022 Jan; 125():103971. PubMed ID: 34920127
[TBL] [Abstract][Full Text] [Related]
23. The quest for better clinical word vectors: Ontology based and lexical vector augmentation versus clinical contextual embeddings.
Nath N; Lee SH; McDonnell MD; Lee I
Comput Biol Med; 2021 Jul; 134():104433. PubMed ID: 34004575
[TBL] [Abstract][Full Text] [Related]
24. Ranking Medical Terms to Support Expansion of Lay Language Resources for Patient Comprehension of Electronic Health Record Notes: Adapted Distant Supervision Approach.
Chen J; Jagannatha AN; Fodeh SJ; Yu H
JMIR Med Inform; 2017 Oct; 5(4):e42. PubMed ID: 29089288
[TBL] [Abstract][Full Text] [Related]
25. Development and evaluation of RapTAT: a machine learning system for concept mapping of phrases from medical narratives.
Gobbel GT; Reeves R; Jayaramaraja S; Giuse D; Speroff T; Brown SH; Elkin PL; Matheny ME
J Biomed Inform; 2014 Apr; 48():54-65. PubMed ID: 24316051
[TBL] [Abstract][Full Text] [Related]
26. Training and intrinsic evaluation of lightweight word embeddings for the clinical domain in Spanish.
Chiu C; Villena F; Martin K; Núñez F; Besa C; Dunstan J
Front Artif Intell; 2022; 5():970517. PubMed ID: 36213168
[TBL] [Abstract][Full Text] [Related]
27. Improved biomedical word embeddings in the transformer era.
Noh J; Kavuluru R
J Biomed Inform; 2021 Aug; 120():103867. PubMed ID: 34284119
[TBL] [Abstract][Full Text] [Related]
28. Visualization of medical concepts represented using word embeddings: a scoping review.
Oubenali N; Messaoud S; Filiot A; Lamer A; Andrey P
BMC Med Inform Decis Mak; 2022 Mar; 22(1):83. PubMed ID: 35351120
[TBL] [Abstract][Full Text] [Related]
29. Optimizing Corpus Creation for Training Word Embedding in Low Resource Domains: A Case Study in Autism Spectrum Disorder (ASD).
Gu Y; Leroy G; Pettygrove S; Galindo MK; Kurzius-Spencer M
AMIA Annu Symp Proc; 2018; 2018():508-517. PubMed ID: 30815091
[TBL] [Abstract][Full Text] [Related]
30. Finding Important Terms for Patients in Their Electronic Health Records: A Learning-to-Rank Approach Using Expert Annotations.
Chen J; Zheng J; Yu H
JMIR Med Inform; 2016 Nov; 4(4):e40. PubMed ID: 27903489
[TBL] [Abstract][Full Text] [Related]
31. Deep learning with sentence embeddings pre-trained on biomedical corpora improves the performance of finding similar sentences in electronic medical records.
Chen Q; Du J; Kim S; Wilbur WJ; Lu Z
BMC Med Inform Decis Mak; 2020 Apr; 20(Suppl 1):73. PubMed ID: 32349758
[TBL] [Abstract][Full Text] [Related]
32. Learning Low-Dimensional Representations of Medical Concepts.
Choi Y; Chiu CY; Sontag D
AMIA Jt Summits Transl Sci Proc; 2016; 2016():41-50. PubMed ID: 27570647
[TBL] [Abstract][Full Text] [Related]
33. Rare Disease Identification from Clinical Notes with Ontologies and Weak Supervision.
Dong H; Suarez-Paniagua V; Zhang H; Wang M; Whitfield E; Wu H
Annu Int Conf IEEE Eng Med Biol Soc; 2021 Nov; 2021():2294-2298. PubMed ID: 34891745
[TBL] [Abstract][Full Text] [Related]
34. A Hybrid Model for Family History Information Identification and Relation Extraction: Development and Evaluation of an End-to-End Information Extraction System.
Kim Y; Heider PM; Lally IR; Meystre SM
JMIR Med Inform; 2021 Apr; 9(4):e22797. PubMed ID: 33885370
[TBL] [Abstract][Full Text] [Related]
35. Extraction of Information Related to Drug Safety Surveillance From Electronic Health Record Notes: Joint Modeling of Entities and Relations Using Knowledge-Aware Neural Attentive Models.
Dandala B; Joopudi V; Tsou CH; Liang JJ; Suryanarayanan P
JMIR Med Inform; 2020 Jul; 8(7):e18417. PubMed ID: 32459650
[TBL] [Abstract][Full Text] [Related]
36. CODER: Knowledge-infused cross-lingual medical term embedding for term normalization.
Yuan Z; Zhao Z; Sun H; Li J; Wang F; Yu S
J Biomed Inform; 2022 Feb; 126():103983. PubMed ID: 34990838
[TBL] [Abstract][Full Text] [Related]
37. A tool for sharing annotated research data: the "Category 0" UMLS (Unified Medical Language System) vocabularies.
Berman JJ
BMC Med Inform Decis Mak; 2003 Jun; 3():6. PubMed ID: 12809560
[TBL] [Abstract][Full Text] [Related]
38. Evaluating Biomedical Word Embeddings for Vocabulary Alignment at Scale in the UMLS Metathesaurus Using Siamese Networks.
Bajaj G; Nguyen V; Wijesiriwardene T; Yip HY; Javangula V; Parthasarathy S; Sheth A; Bodenreider O
Proc Conf Assoc Comput Linguist Meet; 2022 May; 2022():82-87. PubMed ID: 36093038
[TBL] [Abstract][Full Text] [Related]
39. Combining structured and unstructured data for predictive models: a deep learning approach.
Zhang D; Yin C; Zeng J; Yuan X; Zhang P
BMC Med Inform Decis Mak; 2020 Oct; 20(1):280. PubMed ID: 33121479
[TBL] [Abstract][Full Text] [Related]
40. Medical concept normalization in French using multilingual terminologies and contextual embeddings.
Wajsbürt P; Sarfati A; Tannier X
J Biomed Inform; 2021 Feb; 114():103684. PubMed ID: 33450387
[TBL] [Abstract][Full Text] [Related]
[Previous] [Next] [New Search]