Automated mapping of electronic data capture fields to SDTM.
Journal:
PloS one
PMID:
39509395
Abstract
OBJECTIVE: The goal of this work is to reduce the amount of manual work required to go from data capture to regulatory submission. It will be shown that the use of Siamese networks will allow for the generation of embeddings that can be used by traditional machine learning classifiers to perform the classification at much higher levels of accuracy than standard approaches.