Signal Processing in Medicine and Biology : Applications of Deep Learning to the Health Sciences / edited by Ammar Ahmed, Joseph Picone.

Format:

Book

Author/Creator:

Ahmed, Ammar.

Contributor:

Picone, Joseph.

Language:

English

Subjects (All):

Biomedical engineering.

Signal processing.

Imaging systems in biology.

Machine learning.

Biomedical Engineering and Bioengineering.

Digital and Analog Signal Processing.

Biomedical Devices and Instrumentation.

Biological Imaging.

Machine Learning.

Local Subjects:

Biomedical Engineering and Bioengineering.

Digital and Analog Signal Processing.

Biomedical Devices and Instrumentation.

Biological Imaging.

Machine Learning.

Physical Description:

1 online resource (281 pages)

Edition:

1st ed. 2025.

Place of Publication:

Cham : Springer Nature Switzerland : Imprint: Springer, 2025.

Summary:

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; Computational biology; Genomics, genetics, proteomics. Applications of particular interest at the 2023 symposium included digital pathology, computational biology, genomics, genetics, and proteomics. The book features tutorials and examples of successful applications that will appeal to many professionals and researchers in signal processing, medicine, and biology. For students and professionals new to the field, the book offers an easy-to-understand introduction to various bioengineering topics. For professionals active in the field, it provides essential algorithmic details on valuable benchmarks for the technology. Presents an interdisciplinary look at research trends in signal processing and biomedicine; Promotes collaboration between practitioners and researchers; Includes tutorials and examples of successful applications.

Contents:

Introduction

Signal and Image Analysis (EEG, ECG, MRI)

Machine Learning

Data Mining and Classification

Big Data

Index.

ISBN:

3-031-88024-2