Semi-automated Conversion of Clinical Trial Legacy Data into CDISC SDTM Standards Format Using Supervised Machine Learning.
Journal:
Methods of information in medicine
Published Date:
Jul 8, 2021
Abstract
OBJECTIVE: This study aimed to develop a semi-automated process to convert legacy data into clinical data interchange standards consortium (CDISC) study data tabulation model (SDTM) format by combining human verification and three methods: data normalization; feature extraction by distributed representation of dataset names, variable names, and variable labels; and supervised machine learning.