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Titlebook: Data Science for Healthcare; Methodologies and Ap Sergio Consoli,Diego Reforgiato Recupero,Milan Pet Book 2019 Springer Nature Switzerland

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書目名稱Data Science for Healthcare
副標題Methodologies and Ap
編輯Sergio Consoli,Diego Reforgiato Recupero,Milan Pet
視頻videohttp://file.papertrans.cn/264/263119/263119.mp4
概述Connects machine learning, big data analytics, statistics, pattern recognition, computer vision, and Semantic Web technologies to healthcare applications..Highlights the successful application of thes
圖書封面Titlebook: Data Science for Healthcare; Methodologies and Ap Sergio Consoli,Diego Reforgiato Recupero,Milan Pet Book 2019 Springer Nature Switzerland
描述This book seeks to promote the exploitation of data science in healthcare systems. The focus is on advancing the automated analytical methods used to extract new knowledge from data for healthcare applications. To do so, the book draws on several interrelated disciplines, including machine learning, big data analytics, statistics, pattern recognition, computer vision, and Semantic Web technologies, and focuses on their direct application to healthcare..Building on three tutorial-like chapters on data science in healthcare, the following eleven chapters highlight success stories on the application of data science in healthcare, where data science and artificial intelligence technologies have proven to be very promising..This book is primarily intended for data scientists involved in the healthcare or medical sector. By reading this book, they will gain essential insights into the modern data science technologies needed to advance innovation for both healthcare businesses and patients. A basic grasp of data science is recommended in order to fully benefit from this book..??.
出版日期Book 2019
關(guān)鍵詞Data Science; Health Informatics; Machine Learning; Knowledge Management; Data Visualization; Process Ana
版次1
doihttps://doi.org/10.1007/978-3-030-05249-2
isbn_ebook978-3-030-05249-2
copyrightSpringer Nature Switzerland AG 2019
The information of publication is updating

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Making Effective Use of Healthcare Data Using Data-to-Text Technologyl to measure and help achieving these improvements in healthcare delivery. Consequently, a data influx from various clinical, financial, and operational sources is now overtaking healthcare organizations and their patients. The effective use of this data, however, is a major challenge. Clearly, text
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Clinical Natural Language Processing with Deep Learningavailable across healthcare networks. The huge amount of data inspires research and development focused on novel clinical natural language processing (NLP) solutions to optimize clinical care and improve patient outcomes. In recent years, deep learning techniques have demonstrated superior performan
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Assistive Robots for the Elderly: Innovative Tools to Gather Health Relevant Datae way healthcare is delivered. In the research and commercial field, robotic technologies have been used for physical and cognitive rehabilitation, surgery, telemedicine, drug delivery, and patient management. Robots are currently used across a range of environments, including hospitals, homes, scho
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A Flexible Knowledge-Based Architecture for Supporting the Adoption of Healthy Lifestyles with Persu it can significantly contribute to the prevention of chronic diseases deriving from incorrect diet and lack of physical activity. In this chapter, we present the use of Semantic Web technologies to build an architecture for supporting the monitoring of people and for persuading them to follow healt
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