Explainable AI in Drug Discovery and Development - a conversation

The provided text is a comprehensive survey article exploring the use of Explainable Artificial Intelligence (XAI) in drug discovery and development. The article addresses the increasing need for transparency in complex AI and machine learning models used in the healthcare industry. It covers various XAI methods, their application in processes such as target identification and toxicity prediction, and discusses the challenges and limitations of XAI techniques. The survey also emphasizes the ethical considerations and future research directions for XAI in the field. Ultimately, the article aims to provide a deep understanding of how XAI can transform drug discovery by making AI-driven predictions more interpretable and trustworthy.

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