Medical Big Data and Internet of Medical Things

Medical Big Data and Internet of Medical Things: Advances,Challenges and Applications
ISBN-10: 1138492477
ISBN-13: 9781138492479
Edition 版次: 1
Publication Date 出版日期: 2018-10-06
Print Length 页数: 356 pages
Big data and the Internet of Things (IoT) play a vital role in prediction systems used in biological and medical applications,particularly for resolving issues related to disease biology at different scales. Modelling and integrating medical big data with the IoT helps in building effective prediction systems for automatic recommendations of diagnosis and treatment. The ability to mine,process,analyse,characterize,classify and cluster a variety and wide volume of medical data is a challenging task. There is a great demand for the design and development of methods dealing with capturing and automatically analysing medical data from imaging systems and IoT sensors. Addressing analytical and legal issues,and research on integration of big data analytics with respect to clinical practice and clinical utility,architectures and clustering techniques for IoT data processing,effective frameworks for removal of misclassified instances,practicality of big data analytics,methodological and technical issues,potential of Hadoop in managing healthcare data is the need of the hour. This book integrates different aspects used in the field of healthcare such as big data,IoT,soft computing,machine learning,augmented reality,organs on chip,personalized drugs,implantable electronics,integration of bio-interfaces,and wearable sensors,devices,practical body area network (BAN) and architectures of web systems.
Key Features:
Addresses various applications of Medical Big Data and Internet of Medical Things in real time environment
Highlights recent innovations,designs,developments and topics of interest in machine learning techniques for classification of medical data
Provides background and solutions to existing challenges in Medical Big Data and Internet of Medical Things
Provides optimization techniques and programming models to parallelize the computationally intensive tasks in data mining of medical data
Discusses interactions,advantages,limitations,challenges and future perspectives of IoT based remote healthcare monitoring systems.
Includes data privacy and security analysis of cryptography methods for the Web of Medical Things (WoMT)
Presents case studies on the next generation medical chair,electronic nose and pill cam are also presented.
Contents
Preface
Editors
Contributors
Chapter 1: Big Data Mining Methods in Medical
Applications
Chapter 2: Approaches in Healthcare Using Big Data
and Soft Computing
Chapter 3: Implantable Electronics: Integration of
Bio-Interfaces,Devices and Sensors
Chapter 4: Challenges in Designing Software
Architectures for -Web-Based Biomedical Signal
Analysis
Chapter 5: Handling of Medical Imbalanced Big Data
Sets for Improved Classification Using
Adjacent_ Extreme Mix Neighbours Oversampling
Technique (AEMNOST)
Chapter 6: A Big Data Framework for Removing
Misclassified Instances Based on Fuzzy Rough
Chapter 7: Fuzzy C-Mean and Density-Based Spatial
Clustering for Internet of Things Data Processing
Chapter 8: Parallel Data Mining Techniques for Breast
Cancer Prediction
Chapter 9: A MapReduce Approach to Analysing
Healthcare Big Data
Chapter 10: loT and Robotics in Healthcare
Chapter 11: Internet of Medical Things: Remote
Healthcare and Health Monitoring Perspective
Chapter 12: A Comparative Analysis of Classical
Cryptography versus Quantum Cryptography for Web
of Medical Things(WoMT)

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