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. 2019 Nov 12;10(Suppl 1):22. doi: 10.1186/s13326-019-0212-6

Table 5.

MetaMap performance for the candidate terms from VetCN dataset

Target term
(n-gram)
Candidate terms (20 top-ranked n-grams) from CBOW neural embeddings for a target term Candidate terms (20 top-ranked n-grams) from Skip-gram neural embeddings for a target term
MetaMap Experiment 1 MetaMap Experiment 2 MetaMap Experiment 1 MetaMap Experiment 2
P R F P R F P R F P R F
anaemia 84.21 94.12 88.89 95.00 100.00 97.44 94.74 94.74 94.74 95.00 100.00 97.44
arthritis 93.33 73.68 82.35 100.00 75.00 85.71 94.44 89.47 91.89 100.00 90.00 94.74
asthma 100.00 90.00 94.74 100.00 95.00 97.44 89.47 94.44 91.89 100.00 100.00 100.00
ckd 68.75 73.33 70.97 100.00 95.00 97.44 62.50 71.43 66.67 100.00 100.00 100.00
diabetes 76.47 81.25 78.79 100.00 90.00 94.74 88.89 88.89 88.89 94.74 94.74 94.74
epilepsy 100.00 90.00 94.74 100.00 95.00 97.44 100.00 90.00 94.74 100.00 95.00 97.44
glaucoma 87.50 77.78 82.35 94.74 94.74 94.74 93.33 73.68 82.35 94.74 94.74 94.74
heart_failure 73.68 93.33 82.35 95.00 100.00 97.44 84.21 94.12 88.89 100.00 100.00 100.00
hypertension 71.43 62.50 66.67 100.00 95.00 97.44 72.22 86.67 78.79 100.00 100.00 100.00
obesity 75.00 100.00 85.71 85.00 100.00 91.89 84.21 94.12 88.89 89.47 94.44 91.89
osteoarthritis 94.74 94.74 94.74 100.00 95.00 97.44 85.00 100.00 91.89 85.00 100.00 91.89
84.10 84.61 83.85 97.25 94.07 95.38 86.27 88.87 87.24 96.27 97.17 96.63

The table shows the performance of MetaMap in Experiment 1 (applying MetaMap to the candidate terms) and Experiment 2 (short form detection and expansion into long form before applying MetaMap to the candidate terms) for each target term (n-gram for a well-known medical condition). The candidate terms are a list of the 20 top-ranked terms (highest cosine value) obtained from the created neural embeddings with CBOW or Skip-gram taking the vector for a target term. The last row shows the average of each evaluation measure over all 11 medical conditions under study to get an overall measure of performance (a.k.a. macro-averaging). Abbreviations: P = precision; R = recall; and F = F measure