Epilepsy diagnosis using a clinical decision tool and artificially intelligent electroencephalography.

ABSTRACT:

Objective

To construct a tool for non-experts to calculate the probability of epilepsy based on easily obtained clinical information combined with an artificial intelligence readout of the electroencephalogram (AI-EEG).

Materials and methods

We performed a chart review of 205 consecutive patients aged 18 years or older who underwent routine EEG. We created a point system to calculate the pre-EEG probability of epilepsy in a pilot study cohort. We also computed a post-test probability based on AI-EEG results.

Results

One hundred and four (50.7%) patients were female, the mean age was 46 years, and 110 (53.7%) were diagnosed with epilepsy. Findings favoring epilepsy included developmental delay (12.6% vs 1.1%), prior neurological injury (51.4% vs 30.9%), childhood febri

SUBMITTER: McInnis RP 

PROVIDER: S-EPMC10082472 | biostudies-literature | 2023 Apr

REPOSITORIES: biostudies-literature