Sejdic / Falk Signal Processing and Machine Learning for Biomedical Big Data

Erscheinungsjahr 2018
ISBN: 978-1-351-06121-6
Verlag: Taylor & Francis
Format: EPUB
Kopierschutz: Adobe DRM (»Systemvoraussetzungen)

E-Book, Englisch, 624 Seiten

This will be a comprehensive, multi-contributed reference work that will detail the latest research and developments in biomedical signal processing related to big data medical analysis. It will describe signal processing, machine learning, and parallel computing strategies to revolutionize the world of medical analytics and diagnosis as presented by world class researchers and experts in this important field. The chapters will desribe tools that can be used by biomedical and clinical practitioners as well as industry professionals. It will give signal processing researchers a glimpse into the issues faced with Big Medical Data.

Autoren/Hrsg.

Sejdic, Ervin

Falk, Tiago H.

Fachgebiete

• Technische Wissenschaften Verfahrenstechnik | Chemieingenieurwesen | Biotechnologie Biotechnologie Medizinische Biotechnologie
• Technische Wissenschaften Energietechnik | Elektrotechnik Elektrotechnik

Inhaltsverzeichnis

An Introduction to big data in medicine. Big heart data. Predicting asthma-related emergency department visits using big data. Fall detection in homes of older adults using Microsoft Kinect. Visualization analysis for big data in computational cyberpsychology. Heart beats in the cloud. Big Data approaches to trauma outcome prediction. The TUH EEG CORPUS. Big Data reduction using RBFNN. Systems Biology and brain activity. Signal processing to make sense of noisy medical Big Data. Prarallel randomly compressed cubes. Big Data analysis with signal on graphs. Outlying sequence detection in large data sets. Breaking the curse of dimensionality using decompositions. Sparse Fourier transform. Modeling and optimization learning tools for big data analytics. Parallel processing for real-time biomedical big data. Heart beats in the cloud.

Über Autor(innen)

Ervin Sejdic is currently an Assistant Professor with the Department of Electrical Engineering and Biomedical Engineering at the University of Pittsburg. He has extensive research experience in biomedical and theoretical signal processing, swallowing difficulties, gait and balance. assistive technologies, rehabilitation engineering, anticipatory medical devices, and advanced information systems in medicine.

Thiago Falk is the founder and director of the Multimodal Signal Analysis and Enhancement Lab at the University of Quebec in Montreal. His work on signal processing for big multimedia and biomedical data has engenered numerous awards, including the 2015 CMBES Early Career Award and the 2014 WearHacks Creativity Award and the IEEE Kingston Section Ph.D Excellence Award.