Abstract
Deep learning has potential in the process of discovering drug, with enhanced method for analyzing image, structure of molecule and function prediction, along with preset synthesis based on the novel enzymatic structure along tailored features and its applications. Even with expanding quantity based on effective potential approaches, the statistical systems and Machine Learning algorithms that underpin them are sometimes difficult to grasp by the human mind. To meet the required recent paradigm for the automated structure of molecules, for the purpose of 'Explainable Artificial Intelligence' with deep learning approaches. In current era, there is a need for XAI with methods of deep learning to discourse the demand for a developed machine language of the molecular science. This review outlines the important concepts in XAI, possible approaches, and obstacles. It promotes to further development of XAI techniques.
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