A machine-learned analysis suggests non-redundant diagnostic information in olfactory subtests.

ABSTRACT:

Background

The functional performance of the human sense of smell can be approached via assessment of the olfactory threshold, the ability to discriminate odors or the ability to identify odors. Contemporary clinical test batteries include all or a selection of these components, with some dissent about the required number and choice.

Methods

Olfactory thresholds, odor discrimination and odor identification scores were available from 10,714 subjects (3662 with anomia, 4299 with hyposmia, and 2752 with normal olfactory function). To assess, whether the olfactory subtests confer the same information or each subtest confers at least partly non-redundant information relevant to the olfactory diagnosis, we compared the diagnostic accuracy of supervised machine learning algorithms

SUBMITTER: Lotsch J 

PROVIDER: S-EPMC6330373 | biostudies-literature | 2019 Jun

REPOSITORIES: biostudies-literature