Signal Processing in Medicine and Biology - Applications of Deep Learning to the Health Sciences

Signal Processing in Medicine and Biology: Applications of Deep Learning to the Health Sciences presents expanded versions of selected papers from the 2023 IEEE Signal Processing in Medicine and Biology Symposium (IEEE SPMB) at Temple University. The symposium presents multidisciplinary research across a wide range of topics in the life sciences. The Neural Engineering Data Consortium hosts the symposium to promote machine learning and big data applications in bioengineering.
Topics covered include:
·         Signal and image analysis (e.g., EEG, ECG, MRI);
·         Machine learning, data mining, and classification;
·         Big data resources and applications;
·         Applications of quantum computing;
·         Digital pathology;
·       &

List of contents

Introduction.- Signal and Image Analysis (EEG, ECG, MRI).- Machine Learning.- Data Mining and Classification.- Big Data.- Index.

Product details

• Assisted by: Ammar Ahmed (Editor), Picone (Editor), Joseph Picone (Editor)
• Publisher: Springer, Berlin
• Languages: English
• Product format: Hardback
• Release: 28.07.2025
• EAN: 9783031880230
• ISBN: 978-3-0-3188023-0
• No. of pages: 230
• Illustrations: X, 230 p. 62 illus., 50 illus. in color.
• Subjects: Natural sciences, medicine, IT, technology > Technology > Miscellaneous; Elektronik, Analytische Chemie, machine learning, Maschinelles Lernen, Bilderfassungssysteme und -technologie, Digitale Signalverarbeitung (DSP), Artificial Intelligence (AI), Biomedical Engineering and Bioengineering, Digital and Analog Signal Processing, Biomedical Devices and Instrumentation, Neurodegenerative diseases, Machine Learning (ML), Explainable AI (XAI), Biological Imaging, Deep Learning (DL), Digital pathology, Digital Electroencephalography (EEG), Seismocardiographic Signals, Functional Near Infrared Spectroscopy (fNIRS), Neurophysiological Signals