Signal processing and machine learning for biomedical big data
Ervin Sejdic (Editor), Tiago H. Falk (Editor)
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.
eBook, English, 2018
CRC Press, Taylor & Francis Group, Boca Raton, 2018
1 online resource (xviii, 605 pages) : illustrations
9781351061216, 9781498773461, 9781351061209, 9781351061223, 1351061216, 149877346X, 1351061208, 1351061224
1044733829
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.