Machine Learning Applications in Medicine and Biology [electronic resource] / edited by Ammar Ahmed, Joseph Picone.

Colaborador(es): Ahmed, Ammar [editor.] | Picone, Joseph [editor.] | SpringerLink (Online service)Tipo de material: TextoTextoEditor: Cham : Springer Nature Switzerland : Imprint: Springer, 2024Edición: 1st ed. 2024Descripción: V, 168 p. 62 illus., 52 illus. in color. online resourceTipo de contenido: text Tipo de medio: computer Tipo de portador: online resourceISBN: 9783031518935Tema(s): 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 ProcessingFormatos físicos adicionales: Printed edition:: Sin título; Printed edition:: Sin título; Printed edition:: Sin títuloClasificación CDD: 610.28 Clasificación LoC:R856-857Recursos en línea: Libro electrónicoTexto
Contenidos:
Introduction -- Signal and Image Analysis (EEG, ECG, MRI) -- Machine Learning -- Data Mining and Classification -- Big Data -- Index.
En: Springer Nature eBookResumen: 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. .
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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. .

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