PheW²P2V: a phenome-wide prediction framework with weighted patient representations using electronic health records.

ABSTRACT:

Objective

Electronic health records (EHRs) provide opportunities for the development of computable predictive tools. Conventional machine learning methods and deep learning methods have been widely used for this task, with the approach of usually designing one tool for one clinical outcome. Here we developed PheW²P2V, a Phenome-Wide prediction framework using Weighted Patient Vectors. PheW²P2V conducts tailored predictions for phenome-wide phenotypes using numeric representations of patients' past medical records weighted based on their similarities with individual phenotypes.

Materials and methods

PheW²P2V defines clinical disease phenotypes using Phecode mapping based on International Classification of Dis

SUBMITTER: Guo J 

PROVIDER: S-EPMC11401611 | biostudies-literature | 2024 Oct

REPOSITORIES: biostudies-literature