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The structural validation problem using quantum chemistry approaches (confirm or reject a candidate structure) has been tackled with artificial neural network (ANN) mediated multidimensional pattern recognition from experimental and calculated 2D C-H COSY. In order to identify subtle errors (such as regio- or stereochemical), more than 400 ANNs have been built and trained, and the most efficient in terms of classification ability were successfully validated in challenging real examples of natural product misassignments.

GIAO C–H COSY Simulations Merged with Artificial Neural Networks Pattern Recognition Analysis. Pushing the Structural Validation a Step Forward