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We Need Better Benchmarks for Machine Learning in Drug Discovery

Practical Cheminformatics

Most papers describing new methods for machine learning (ML) in drug discovery report some sort of benchmark comparing their algorithm and/or molecular representation with the current state of the art. Many authors have simply classified any drugs used for psychiatric indications or drugs with side effects such as drowsiness as CNS penetrant.

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