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Big data analytics and machine intelligence in biomedical and health informaticsconcepts, methodologies, tools and applications /

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Big data analytics and machine intelligence in biomedical and health informaticsedited by Sunil Kumar Dhal ... [et al.]
其他題名:	concepts, methodologies, tools and applications /
其他作者:	Dhal, Sunil Kumar.
出版者:	Hoboken, NJ :John Wiley & Sons ;2022.
面頁冊數:	1 online resource :ill. (chiefly col.)
標題:	Artificial intelligence.
電子資源:	https://onlinelibrary.wiley.com/doi/book/10.1002/9781119792376
ISBN:	9781119792376$q(electronic bk. : oBook)

Big data analytics and machine intelligence in biomedical and health informaticsconcepts, methodologies, tools and applications /
Big data analytics and machine intelligence in biomedical and health informaticsconcepts, methodologies, tools and applications /[electronic resource] :edited by Sunil Kumar Dhal ... [et al.] - 1st ed. - Hoboken, NJ :John Wiley & Sons ;2022. - 1 online resource :ill. (chiefly col.)

Includes bibliographical references and index.

BIG DATA ANALYTICS AND MACHINE INTELLIGENCE IN BIOMEDICAL AND HEALTH INFORMATICS Provides coverage of developments and state-of-the-art methods in the broad and diversified data analytics field and applicable areas such as big data analytics, data mining, and machine intelligence in biomedical and health informatics. The novel applications of Big Data Analytics and machine intelligence in the biomedical and healthcare sector is an emerging field comprising computer science, medicine, biology, natural environmental engineering, and pattern recognition. Biomedical and health informatics is a new era that brings tremendous opportunities and challenges due to the plentifully available biomedical data and the aim is to ensure high-quality and efficient healthcare by analyzing the data. The 12 chapters in??Big Data Analytics and Machine Intelligence in Biomedical and Health Informatics??cover the latest advances and developments in health informatics, data mining, machine learning, and artificial intelligence. They have been organized with respect to the similarity of topics addressed, ranging from issues pertaining to the Internet of Things (IoT) for biomedical engineering and health informatics, computational intelligence for medical data processing, and Internet of Medical Things??(IoMT). New researchers and practitioners working in the field will benefit from reading the book as they can quickly ascertain the best performing methods and compare the different approaches. Audience Researchers and practitioners working in the fields of biomedicine, health informatics, big data analytics, Internet of Things, and machine learning.

ISBN: 9781119792376$q(electronic bk. : oBook)

Standard No.: 10.1002/9781119792376doiSubjects--Topical Terms:

194058
Artificial intelligence.

LC Class. No.: R858 / .B54 2022

Dewey Class. No.: 610.285

Big data analytics and machine intelligence in biomedical and health informaticsconcepts, methodologies, tools and applications /
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300 $a 1 online resource : $b ill. (chiefly col.)
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520 $a BIG DATA ANALYTICS AND MACHINE INTELLIGENCE IN BIOMEDICAL AND HEALTH INFORMATICS Provides coverage of developments and state-of-the-art methods in the broad and diversified data analytics field and applicable areas such as big data analytics, data mining, and machine intelligence in biomedical and health informatics. The novel applications of Big Data Analytics and machine intelligence in the biomedical and healthcare sector is an emerging field comprising computer science, medicine, biology, natural environmental engineering, and pattern recognition. Biomedical and health informatics is a new era that brings tremendous opportunities and challenges due to the plentifully available biomedical data and the aim is to ensure high-quality and efficient healthcare by analyzing the data. The 12 chapters in??Big Data Analytics and Machine Intelligence in Biomedical and Health Informatics??cover the latest advances and developments in health informatics, data mining, machine learning, and artificial intelligence. They have been organized with respect to the similarity of topics addressed, ranging from issues pertaining to the Internet of Things (IoT) for biomedical engineering and health informatics, computational intelligence for medical data processing, and Internet of Medical Things??(IoMT). New researchers and practitioners working in the field will benefit from reading the book as they can quickly ascertain the best performing methods and compare the different approaches. Audience Researchers and practitioners working in the fields of biomedicine, health informatics, big data analytics, Internet of Things, and machine learning.
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