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A Textbook On ARTIFICIAL INTELLIGENCE IN PRECISION MEDICINE, DRUG DEVELOPMENT, AND HEALTHCARE
註釋I would like to take this opportunity to expose you to the topic of "Artificial Intelligence in Precision Medicine, Drug Development, and Healthcare." Artificial intelligence (AI) is one of the most revolutionary forces that will shape the future of medicine and healthcare delivery, and this book is a comprehensive investigation of that force. In recent years, artificial intelligence has emerged as a strong technology that has the ability to revolutionise every area of the healthcare ecosystem. This includes personalized treatment plans, medication discovery and development, and even the delivery of healthcare services. At the convergence of artificial intelligence and precision medicine lies the potential of healthcare solutions that are more effective, efficient, and equitable, and that are personalized to the specific requirements of each individual patient. The purpose of this book is to take us on a trip to reveal the intricacies of artificial intelligence in the healthcare industry by investigating its applications, problems, and ethical implications. In this article, we delve into the complexities of precision medicine, which is using artificial intelligence to provide clinicians with insights that enable them to give customised treatments based on a patient's unique genetic composition, lifestyle characteristics, and environmental impacts. In addition, we investigate the role that artificial intelligence plays in the process of drug discovery and development. This is a process in which sophisticated algorithms and machine learning models speed up the process of identifying innovative drug candidates, optimise the design of clinical trials, and improve the safety and effectiveness of pharmaceutical interventions. A new era of innovation is being ushered in by artificial intelligence, which is transforming the landscape of the pharmaceutical sector in a variety of ways, including medication repurposing and predictive modelling of drug toxicity.