CompleteRXN: A Method for Filling Gaps in Open Chemical Reaction Databases

Summary

This academic paper from Delft University of Technology researchers addresses the problem of incompleteness in chemical reaction datasets like USPTO. The authors present "CompleteRXN," a methodology to identify and fill missing information in open chemical reaction databases. The work focuses on improving data quality for machine learning applications in chemistry by detecting incomplete reactions and suggesting completions, ultimately aiming to make chemical reaction data more reliable and useful for computational research.