Titlebook: Artificial Intelligence in Medicine; Niklas Lidstr?mer,Hutan Ashrafian Reference work 2022 Springer Nature Switzerland AG 2022 Deep Medici

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Basic Concepts of Artificial Intelligence: Primed for Clinicians on crucial tasks, artificial intelligence algorithms were introduced..An expansive demand of AI applications in varying fields led to the development of specifically designed ad hoc algorithms with the role of better estimating (by learning) solutions to the problems..The boost of AI in healthcare

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Applying Principles from Medicine Back to Artificial Intelligenceportant one also—many of the breakthroughs in the field of AI are due to knowledge and inspiration . biology, psychology, and encompassing medical sciences. The artificial neuron, one of the first achievements in AI, is discussed. Knowledge about the visual cortex inspiring the creation of the neoco

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Mathematical Foundations of AIMess of deep learning in medical imaging, these recent developments are largely empirical. Our goal in this chapter is to provide an overview of some of the key mathematical foundations of deep learning to the medical imaging community. In particular, we will consider ties with traditional machine le

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Introductory Approaches for Applying Artificial Intelligence in Clinical Medicineical purposes have brought the necessity to introduce artificial intelligence algorithms to healthcare..The first artificial intelligence applications in the medical field were to be seen in the introduction of Electronic Health Records followed by the development of Learning Health Systems and Clin

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Importance of AI in Medicine of practitioners in computer graphics, image processing, and computer science. The entry of large corporations, attempting to simplify and streamline machine learning, creates an environment providing for reduced technical understanding by users. Competition for noteworthy breakthroughs drive rapid

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Artificial Intelligence in Medicine and Privacy Preservationve datasets. So far, such datasets have only been able to be assembled through multi-institutional data sharing and aggregation. Such practices are however associated with legal, ethical, and technical challenges and scale poorly to multinational efforts. They furthermore potentially infringe on dat