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Table 1 A brief summary of several clinical concept embedding studies. Only the largest database used in the study was listed

From: Time-sensitive clinical concept embeddings learned from large electronic health records

Study Method Data source patient size Time-sensitive Evaluation strategies
Med2vec [10] word2vec EHR/ claims < 1 million No Similarity based on vocabularies, predictive modeling and human assessment
Cui2vec [11] word2vec, glove claims 60 million Only in negative sampling for word2vec Similarity based on vocabularies and human assessment
MCE [13] attention- word2vec EHR < 2 million With an attention layer Similarity based on vocabularies
Ours’ word2vec, PMIa, FastText EHR 50 million Dynamic input windows Similarity based on vocabularies, and predictive \modeling
  1. apointwise mutual information