Diagnosis of Acute Central Dizziness With Simple Clinical Information Using Machine Learning.

ABSTRACT: Background: Acute dizziness is a common symptom among patients visiting emergency medical centers. Extensive neurological examinations aimed at delineating the cause of dizziness often require experience and specialized training. We tried to diagnose central dizziness by machine learning using only basic clinical information. Methods: Patients were enrolled who had visited an emergency medical center with acute dizziness and underwent diffusion-weighted imaging. The enrolled patients were dichotomized as either having central (with a corresponding central lesion) or non-central dizziness. We obtained patient demographics, risk factors, vital signs, and presentation (non-whirling type dizziness or vertigo). Various machine learning algorithms were used to predict central dizzi

SUBMITTER: Kim BJ 

PROVIDER: S-EPMC8313110 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature