Use of word and graph embedding to measure semantic relatedness between Unified Medical Language System concepts

• Published in: Journal of the American Medical Informatics Association : JAMIA Vol. 27; no. 10; pp. 1538 - 1546
• Main Authors: Mao, Yuqing, Fung, Kin Wah
• Format: Journal Article
• Language: English
• Published: England Oxford University Press 01.10.2020
• Subjects: Deep Learning; Medical Subject Headings; Natural Language Processing; Research and Applications; ROC Curve; Semantics; Terminology as Topic; Unified Medical Language System; UMLS; deep learning; graph embedding; semantic relatedness; medical terminologies; word embedding

Abstract Objective The study sought to explore the use of deep learning techniques to measure the semantic relatedness between Unified Medical Language System (UMLS) concepts. Materials and Methods Concept sentence embeddings were generated for UMLS concepts by applying the word embedding models Bio...