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Artificial intelligence in medical i...

Morra, Lia.

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Artificial intelligence in medical imaging = from theory to clinical practice /

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Artificial intelligence in medical imaging/ Lia Morra, Silvia Delsanto, Loredana Correale.
其他題名:	from theory to clinical practice /
作者:	Morra, Lia.
其他作者:	Delsanto, Silvia.
出版者:	Boca Raton, FL :CRC Press, : c2020.,
面頁冊數:	1 online resource.
內容註:	Fundamentals of machine learning -- Introduction to deep learning -- Applying AI in medical imaging -- Designing AI systems for the clinical practice -- Future perspectives.
標題:	Diagnostic imaging. -
電子資源:	https://www.taylorfrancis.com/books/9780367229184
ISBN:	9780367229184

Artificial intelligence in medical imaging = from theory to clinical practice /
Morra, Lia.

Artificial intelligence in medical imagingfrom theory to clinical practice /[electronic resource] :Lia Morra, Silvia Delsanto, Loredana Correale. - Boca Raton, FL :CRC Press,c2020. - 1 online resource.

Includes bibliographical references and index.

Fundamentals of machine learning -- Introduction to deep learning -- Applying AI in medical imaging -- Designing AI systems for the clinical practice -- Future perspectives.

"This book, written by authors with more than a decade of experience in the design and development of artificial intelligence (AI) systems in medical imaging, will guide readers in the understanding of one of the most exciting fields today. After an introductory description of classical machine learning techniques, the fundamentals of deep learning are explained in a simple yet comprehensive manner. The book then proceeds with a historical perspective of how medical AI developed in time, detailing which applications triumphed and which failed, from the era of computer aided detection systems on to the current cutting-edge applications in deep learning today, which are starting to exhibit on-par performance with clinical experts. In the last section, the book offers a view on the complexity of the validation of artificial intelligence applications for commercial use, describing the recently introduced concept of software as a medical device, as well as good practices and relevant considerations for training and testing machine learning systems for medical use. Open problematics on the validation for public use of systems which by nature continuously evolve through new data is also explored. The book will be of interest to graduate students in medical physics, biomedical engineering and computer science, in addition to researchers and medical professionals operating in the medical imaging domain, who wish to better understand these technologies and the future of the field. Features: An accessible yet detailed overview of the field Explores a hot and growing topic Provides an interdisciplinary perspective"--

ISBN: 9780367229184

LCCN: 2019723440Subjects--Topical Terms:

658032
Diagnostic imaging.

LC Class. No.: RC78.7.D53

Dewey Class. No.: 616.07/54

Artificial intelligence in medical imaging = from theory to clinical practice /
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505 0 $a Fundamentals of machine learning -- Introduction to deep learning -- Applying AI in medical imaging -- Designing AI systems for the clinical practice -- Future perspectives.
520 $a "This book, written by authors with more than a decade of experience in the design and development of artificial intelligence (AI) systems in medical imaging, will guide readers in the understanding of one of the most exciting fields today. After an introductory description of classical machine learning techniques, the fundamentals of deep learning are explained in a simple yet comprehensive manner. The book then proceeds with a historical perspective of how medical AI developed in time, detailing which applications triumphed and which failed, from the era of computer aided detection systems on to the current cutting-edge applications in deep learning today, which are starting to exhibit on-par performance with clinical experts. In the last section, the book offers a view on the complexity of the validation of artificial intelligence applications for commercial use, describing the recently introduced concept of software as a medical device, as well as good practices and relevant considerations for training and testing machine learning systems for medical use. Open problematics on the validation for public use of systems which by nature continuously evolve through new data is also explored. The book will be of interest to graduate students in medical physics, biomedical engineering and computer science, in addition to researchers and medical professionals operating in the medical imaging domain, who wish to better understand these technologies and the future of the field. Features: An accessible yet detailed overview of the field Explores a hot and growing topic Provides an interdisciplinary perspective"-- $c Provided by publisher.
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