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Biomedical Information Technology. Edition No. 2. Biomedical Engineering

  • ID: 4768574
  • Book
  • October 2019
  • Region: Global
  • 820 Pages
  • Elsevier Science and Technology
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Biomedical Information Technology, Second Edition, contains practical, integrated clinical applications for disease detection, diagnosis, surgery, therapy and biomedical knowledge discovery, including the latest advances in the field, such as biomedical sensors, machine intelligence, artificial intelligence, deep learning in medical imaging, neural networks, natural language processing, large-scale histopathological image analysis, virtual, augmented and mixed reality, neural interfaces, and data analytics and behavioral informatics in modern medicine. The enormous growth in the field of biotechnology necessitates the utilization of information technology for the management, flow and organization of data.

All biomedical professionals can benefit from a greater understanding of how data can be efficiently managed and utilized through data compression, modeling, processing, registration, visualization, communication and large-scale biological computing.

  • Presents the world's most recognized authorities who give their "best practices"
  • Provides professionals with the most up-to-date and mission critical tools to evaluate the latest advances in the field
  • Gives new staff the technological fundamentals and updates experienced professionals with the latest practical integrated clinical applications

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1. Medical Imaging
2. Biomedical Sensors
3. Biologic Computing
4. Electronic Medical Records and Picture Archive and Communication Systems (PACS)
5. Machine Intelligence in Medical Imaging
6. Health Intelligence
7. Artificial Intelligence in Bioinformatics
8. Deep Learning in Medical Image Analysis
9. Automatic Lesion Detection with 3D Convolutional Neural Networks
10. Biomedical Image Segmentation for Precision Radiation Oncology
11. Content-based Large-Scale Medical Image Retrieval
12. Natural Language Processing for Big Medical Data Analytics
13. Towards Large-Scale Histopathological Image Analysis
14. Biomedical Data Modelling and Parametric Imaging
15. Biomedical Data and Information Visualization
16. Biomedical Image Characterization and Radiogenomics
17. Medical Robotics
18. Clinical Virtual Reality: A Brief Review of the Future
19. Social and Affective Robotics for Neurodisorder Therapy
20. Telehealth and mHealth Computing
21. Internet of Things in Healthcare
22. Social Media for Healthcare
23. Data Analytics and Behavior Informatics in Modern Healthcare
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Feng, David Dagan
Professor David Dagan Feng is Founder and Director, Biomedical and Multimedia Information Technology (BMIT) Research Group, Funding Director, Institute of Biomedical Engineering & Technology (BMET), and Funding Head, School of Information Technology (recently renamed as School of Computer Science), the University of Sydney (USYD), as well as Academic Director, USYD-SJTU (Shanghai Jiao Tong University) Joint Research Alliance. He has been, Head of Department of Computer Science and Associate Dean, Faculty of Science, the University of Sydney; Honorary Research Consultant, Royal Prince Alfred Hospital, the largest hospital in Australia; Chair Professor of Information Technology, Hong Kong Polytechnic University; Scientific Advisor, the 3D Anatomical Human European Institute / Project involving 7 countries; Advisory Professor, Chief Scientist and Chair of the International Advisory Committee, Med-X Research Institute, Shanghai Jiao Tong University; Guest Professor for a number of universities, including Tsinghua University. He received his M.E. in Electrical Engineering & Computer Science (EECS) from Shanghai Jiao Tong University in 1982, M.Sc. in Biocybernetics and Ph.D. in Computer Science from the University of California, Los Angeles (UCLA) in 1985 and 1988, respectively, where he received the Crump Prize for Excellence in Medical Engineering. In conjunction with his team members and students, he has been responsible for more than 50 key research projects, published over 900 scholarly research papers, pioneered several new research directions, and made a number of landmark contributions in his field. He has served as Chair of the International Federation of Automatic Control (IFAC) Technical Committee on Biological and Medical Systems, Special Area Editor / Associate Editor / Editorial Board Member for a dozen of core journals in his area, and Scientific Advisor for a number of prestigious organizations. He has been invited to give over 100 keynote presentations in 23 countries and regions, and has organized / chaired over 100 major international conferences / symposia / workshops. Professor Feng is Fellow of ACS, HKIE, IET, IEEE, and Australian Academy of Technological Sciences and Engineering.
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