Machine Learning Applications in Medicine and Biology
Machine Learning Applications in Medicine and Biology [electronic resource] /
edited by Ammar Ahmed, Joseph Picone.
- 1st ed. 2024.
- V, 168 p. 62 illus., 52 illus. in color. online resource.
Introduction -- Signal and Image Analysis (EEG, ECG, MRI) -- Machine Learning -- Data Mining and Classification -- Big Data -- Index.
This book combines selected papers from the 2022 IEEE Signal Processing in Medicine and Biology Symposium (IEEE SPMB) held at Temple University. The symposium presents multidisciplinary research in the life sciences. Topics covered include: Signal and image analysis (EEG, ECG, MRI) Machine learning Data mining and classification Big data resources Applications of particular interest at the 2022 symposium included digital pathology, computational biology, and quantum computing. The book features tutorials and examples of successful applications that will appeal to a wide range of professionals and researchers in signal processing, medicine, and biology. Presents an interdisciplinary look at research trends; Promotes collaboration between practitioners and researchers; Includes tutorials and examples of successful applications. .
9783031518935
Biomedical engineering.
Imaging systems in biology.
Machine learning.
Signal processing.
Biomedical Engineering and Bioengineering.
Biological Imaging.
Machine Learning.
Biomedical Devices and Instrumentation.
Digital and Analog Signal Processing.
R856-857
610.28
Introduction -- Signal and Image Analysis (EEG, ECG, MRI) -- Machine Learning -- Data Mining and Classification -- Big Data -- Index.
This book combines selected papers from the 2022 IEEE Signal Processing in Medicine and Biology Symposium (IEEE SPMB) held at Temple University. The symposium presents multidisciplinary research in the life sciences. Topics covered include: Signal and image analysis (EEG, ECG, MRI) Machine learning Data mining and classification Big data resources Applications of particular interest at the 2022 symposium included digital pathology, computational biology, and quantum computing. The book features tutorials and examples of successful applications that will appeal to a wide range of professionals and researchers in signal processing, medicine, and biology. Presents an interdisciplinary look at research trends; Promotes collaboration between practitioners and researchers; Includes tutorials and examples of successful applications. .
9783031518935
Biomedical engineering.
Imaging systems in biology.
Machine learning.
Signal processing.
Biomedical Engineering and Bioengineering.
Biological Imaging.
Machine Learning.
Biomedical Devices and Instrumentation.
Digital and Analog Signal Processing.
R856-857
610.28
