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The advent of artificial intelligence (AI) has brought about a paradigm shift in numerous fields. AI technologies can process vast amounts of data, recognize intricate patterns, and generate predictive models. These features are all particularly useful in the field of medical research.

This publication provides a comprehensive review of the current state of AI in medical research. It aims to educate researchers, healthcare professionals, and the general public, on how AI is used in the healthcare industry. It delves into AI's role in drug discovery, encompassing de novo drug design, retrosynthesis, reaction prediction, and protein engineering. It also explores AI's role in diagnosis and personalized medicine, focusing on the concept of a Cognitive Digital Twin.

Additionally, this document examines the ethical and legal challenges with AI in medical research. These challenges include data privacy, algorithmic bias, informed consent, safety, and liability, emphasizing the need for up-to-date regulatory frameworks and interdisciplinary collaboration. 

Overall, this publication helps ensure the responsible and effective integration of AI in the medical field, ultimately improving patient outcomes and healthcare delivery.