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Название: A Handbook of Artificial Intelligence in Drug Delivery
Автор: Anil K. Philip, Aliasgar Shahiwala, Md. Faiyazuddin
Издательство: Academic Press/Elsevier
Год: 2023
Страниц: 623
Язык: английский
Формат: pdf (true)
Размер: 29.3 MB
A Handbook of Artificial Intelligence in Drug Delivery explores the use of Artificial Intelligence (AI) in drug delivery strategies. The book covers pharmaceutical AI and drug discovery challenges, Artificial Intelligence tools for drug research, AI enabled intelligent drug delivery systems and next generation novel therapeutics, broad utility of AI for designing novel micro/nanosystems for drug delivery, AI driven personalized medicine and Gene therapy, 3D Organ printing and tissue engineering, Advanced nanosystems based on AI principles (nanorobots, nanomachines), opportunities and challenges using artificial intelligence in ADME/Tox in drug development, commercialization and regulatory perspectives, ethics in AI, and more. Machine Learning (ML) is a subset of the umbrella term Artificial Intelligence (AI). AI has already crept into several tasks of our day-to-day life, like digital assistants, internet surfing, online shopping, etc. Machine learning (ML), as the name indicates, is a way (algorithm) of self-learning by computer. The development of ML algorithms originated from the quest of computers that learn on their own based on their experiences. The learning takes place with the help of a dataset provided to the computer as training data.
Автор: Anil K. Philip, Aliasgar Shahiwala, Md. Faiyazuddin
Издательство: Academic Press/Elsevier
Год: 2023
Страниц: 623
Язык: английский
Формат: pdf (true)
Размер: 29.3 MB
A Handbook of Artificial Intelligence in Drug Delivery explores the use of Artificial Intelligence (AI) in drug delivery strategies. The book covers pharmaceutical AI and drug discovery challenges, Artificial Intelligence tools for drug research, AI enabled intelligent drug delivery systems and next generation novel therapeutics, broad utility of AI for designing novel micro/nanosystems for drug delivery, AI driven personalized medicine and Gene therapy, 3D Organ printing and tissue engineering, Advanced nanosystems based on AI principles (nanorobots, nanomachines), opportunities and challenges using artificial intelligence in ADME/Tox in drug development, commercialization and regulatory perspectives, ethics in AI, and more. Machine Learning (ML) is a subset of the umbrella term Artificial Intelligence (AI). AI has already crept into several tasks of our day-to-day life, like digital assistants, internet surfing, online shopping, etc. Machine learning (ML), as the name indicates, is a way (algorithm) of self-learning by computer. The development of ML algorithms originated from the quest of computers that learn on their own based on their experiences. The learning takes place with the help of a dataset provided to the computer as training data.