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Titlebook: Prognostic Models in Healthcare: AI and Statistical Approaches; Tanzila Saba,Amjad Rehman,Sudipta Roy Book 2022 The Editor(s) (if applicab

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書目名稱Prognostic Models in Healthcare: AI and Statistical Approaches
編輯Tanzila Saba,Amjad Rehman,Sudipta Roy
視頻videohttp://file.papertrans.cn/760/759820/759820.mp4
概述Presents significant technological breakthroughs and research results in predictive modeling.Contains high-quality, original work that will assist readers in realizing novel applications and contexts.
叢書名稱Studies in Big Data
圖書封面Titlebook: Prognostic Models in Healthcare: AI and Statistical Approaches;  Tanzila Saba,Amjad Rehman,Sudipta Roy Book 2022 The Editor(s) (if applicab
描述This book focuses on contemporary technologies and research in computational intelligence that has reached the practical level and is now accessible in preclinical and clinical settings. This book‘s principal objective is to thoroughly understand significant technological breakthroughs and research results in predictive modeling in healthcare imaging and data analysis. Machine learning and deep learning could be used to fully automate the diagnosis and prognosis of patients in medical fields. The healthcare industry‘s emphasis has evolved from a clinical-centric to a patient-centric model. However, it is still facing several technical, computational, and ethical challenges. Big data analytics in health care is becoming a revolution in technical as well as societal well-being viewpoints.? Moreover, in this age of big data, there is increased access to massive amounts of regularly gathered data from the healthcare industry that has necessitated the development of predictive models and automated solutions for the early identification of critical and chronic illnesses. The book contains high-quality, original work that will assist readers in realizing novel applications and contexts fo
出版日期Book 2022
關(guān)鍵詞Prognostic Modelling; Healthcare Informatics; Image and Data Analysis; Deep Neural Network; Supervised L
版次1
doihttps://doi.org/10.1007/978-981-19-2057-8
isbn_softcover978-981-19-2059-2
isbn_ebook978-981-19-2057-8Series ISSN 2197-6503 Series E-ISSN 2197-6511
issn_series 2197-6503
copyrightThe Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapor
The information of publication is updating

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