Development and Validation of a Deep Learning Model for Predicting Treatment Response in Patients With Newly Diagnosed Epilepsy.

ABSTRACT:

Importance

Selection of antiseizure medications (ASMs) for epilepsy remains largely a trial-and-error approach. Under this approach, many patients have to endure sequential trials of ineffective treatments until the "right drugs" are prescribed.

Objective

To develop and validate a deep learning model using readily available clinical information to predict treatment success with the first ASM for individual patients.

Design, setting, and participants

This cohort study developed and validated a prognostic model. Patients were treated between 1982 and 2020. All patients were followed up for a minimum of 1 year or until failure of the first ASM. A total of 2404 adults with epilepsy newly treated at specialist clinics in Scotland, Malaysia, Australia, and China between 198

SUBMITTER: Hakeem H 

PROVIDER: S-EPMC9425285 | biostudies-literature | 2022 Oct

REPOSITORIES: biostudies-literature