计算机科学
词典
词汇
窗口(计算)
词(群论)
嵌入
自然语言处理
质量(理念)
人工智能
万维网
语言学
认识论
哲学
作者
Maxim Topaz,Ludmila Murga,Ofrit Bar‐Bachar,Margaret V. McDonald,Kathryn H. Bowles
出处
期刊:Cin-computers Informatics Nursing
日期:2019-09-02
卷期号:37 (11): 583-590
被引量:31
标识
DOI:10.1097/cin.0000000000000557
摘要
This study develops and evaluates an open-source software (called NimbleMiner) that allows clinicians to interact with word embedding models with a goal of creating lexicons of similar terms. As a case study, the system was used to identify similar terms for patient fall history from homecare visit notes (N = 1 149 586) extracted from a large US homecare agency. Several experiments with parameters of word embedding models were conducted to identify the most time-effective and high-quality model. Models with larger word window width sizes (n = 10) that present users with about 50 top potentially similar terms for each (true) term validated by the user were most effective. NimbleMiner can assist in building a thorough vocabulary of fall history terms in about 2 hours. For domains like nursing, this approach could offer a valuable tool for rapid lexicon enrichment and discovery.
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