PhD Thesis Defense: Machine Learning in Drug Discovery

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This academic paper explores the integration of machine learning in drug discovery, emphasizing its importance and addressing key gaps in existing methods. It outlines research objectives, methodologies including data collection, modeling, and evaluation metrics, and identifies novel strategies and validations. The work highlights practical applications through case studies and discusses broader implications, challenges, and future directions. A comprehensive literature review, key findings,...