Search Articles

View query in Help articles search
e.g. John Smith or 0000-0001-6479-5330

Search Results (1 to 8 of 8 Results)

Download search results: CSV END BibTex RIS

Ranking Medical Terms to Support Expansion of Lay Language Resources for Patient Comprehension of Electronic Health Record Notes: Adapted Distant Supervision Approach

Ranking Medical Terms to Support Expansion of Lay Language Resources for Patient Comprehension of Electronic Health Record Notes: Adapted Distant Supervision Approach

We represented multiword terms (ie, compound terms) by the mean of the vectors of their component words by following Jagannatha et al [37] and Chen and colleagues [38,39]. We mapped candidate terms to UMLS concepts and included semantic types for those concepts that had an exact match or a head-noun match as features. Each semantic type is a 0-1 binary feature. This type of feature has been used to identify domain-specific medical terms [23,33] and to rank medical terms from individual EHR notes [38].

Jinying Chen, Abhyuday N Jagannatha, Samah J Fodeh, Hong Yu

JMIR Med Inform 2017;5(4):e42

Download Citation: END BibTex RIS

Download PDF Download XML
Article has an altmetric score of 4

Finding Important Terms for Patients in Their Electronic Health Records: A Learning-to-Rank Approach Using Expert Annotations

Finding Important Terms for Patients in Their Electronic Health Records: A Learning-to-Rank Approach Using Expert Annotations

Reference 64: Mikolov T, Chen K, Corrado G, Dean J(https://www.researchgate.net/profile/Gs_Corrado/publication

Jinying Chen, Jiaping Zheng, Hong Yu

JMIR Med Inform 2016;4(4):e40

Download Citation: END BibTex RIS

Download PDF Download XML
Article has an altmetric score of 1