An algorithm as a diagnostic tool for central ocular motor disorders, also to diagnose rare disorders.

ABSTRACT:

Background

Recently an increasing number of digital tools to aid clinical work have been published. This study's aim was to create an algorithm which can assist physicians as a "digital expert" with the differential diagnosis of central ocular motor disorders, in particular in rare diseases.

Results

The algorithm's input consists of a maximum of 60 neurological and oculomotor signs and symptoms. The output is a list of the most probable diagnoses out of 14 alternatives and the most likely topographical anatomical localizations out of eight alternatives. Positive points are given for disease-associated symptoms, negative points for symptoms unlikely to occur with a disease. The accuracy of the algorithm was evaluated using the two diagnoses and two brain zones with the highes

SUBMITTER: Kraus L 

PROVIDER: S-EPMC6688379 | biostudies-literature | 2019 Aug

REPOSITORIES: biostudies-literature