A predictive analytics model for differentiating between transient ischemic attacks (TIA) and its mimics.

ABSTRACT:

Background

Transient ischemic attack (TIA) is a brief episode of neurological dysfunction resulting from cerebral ischemia not associated with permanent cerebral infarction. TIA is associated with high diagnostic errors because of the subjective nature of findings and the lack of clinical and imaging biomarkers. The goal of this study was to design and evaluate a novel multinomial classification model, based on a combination of feature selection mechanisms coupled with logistic regression, to predict the likelihood of TIA, TIA mimics, and minor stroke.

Methods

We conducted our modeling on consecutive patients who were evaluated in our health system with an initial diagnosis of TIA in a 9-month period. We established the final diagnoses after the clinical evaluation by indepe

SUBMITTER: Stanciu A 

PROVIDER: S-EPMC7302339 | biostudies-literature | 2020 Jun

REPOSITORIES: biostudies-literature