Pretrained Medical Representations for the Practical Screening of Drug Repositioning Candidates

Researchers have developed a new method for learning representations from medical code sequences in electronic health records to help identify existing drugs that could treat different conditions. By improving how clinical data is processed, this approach aims to streamline the drug repositioning pipeline and reduce the manual labor required for early-stage screening.