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Table 1 Abnormal annotation distribution

From: Temporal bone radiology report classification using open source machine learning and natural langue processing libraries

Region

Training set

Test set

At least one

62.41 % (362)

62.33 % (91)

Inner

26.72 % (155)

26.03 % (38)

Middle

37.59 % (218)

40.41 % (59)

Outer

13.79 % (80)

14.38 % (21)

Mastoid

30.86 % (179)

36.99 % (54)

  1. Column values indicate the percentage of documents (values in parenthesis indicate absolute number of documents) that were labeled as abnormal for the given region. A document as a whole was considered abnormal if it contained an abnormality in at least one region. The training and test sets contain a total of 580 and 146 documents, respectively
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BMC Medical Informatics and Decision Making

ISSN: 1472-6947

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