An artificial intelligence-based approach for identifying rare disease patients using retrospective electronic health records applied for Pompe disease.

ABSTRACT:

Objective

We retrospectively screened 350,116 electronic health records (EHRs) to identify suspected patients for Pompe disease. Using these suspected patients, we then describe their phenotypical characteristics and estimate the prevalence in the respective population covered by the EHRs.

Methods

We applied Symptoma's Artificial Intelligence-based approach for identifying rare disease patients to retrospective anonymized EHRs provided by the "University Hospital Salzburg" clinic group. Within 1 month, the AI screened 350,116 EHRs reaching back 15 years from five hospitals, and 104 patients were flagged as probable for Pompe disease. Flagged patients were manually reviewed and assessed by generalist and specialist physicians for their likelihood for Pompe disease, from which

SUBMITTER: Lin S 

PROVIDER: S-EPMC10160659 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature