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Machine learning applications in medicine and biology

Record Type:	Electronic resources : Monograph/item
Title/Author:	Machine learning applications in medicine and biologyedited by Ammar Ahmed, Joseph Picone.
other author:	Ahmed, Ammar.
Published:	Cham :Springer Nature Switzerland :2024.
Description:	v, 168 p. :ill. (some col.), digital ;24 cm.
Contained By:	Springer Nature eBook
Subject:	Machine learningCongresses.
Online resource:	https://doi.org/10.1007/978-3-031-51893-5
ISBN:	9783031518935$q(electronic bk.)

Machine learning applications in medicine and biology
Machine learning applications in medicine and biology[electronic resource] /edited by Ammar Ahmed, Joseph Picone. - Cham :Springer Nature Switzerland :2024. - v, 168 p. :ill. (some col.), digital ;24 cm.

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.

ISBN: 9783031518935$q(electronic bk.)

Standard No.: 10.1007/978-3-031-51893-5doiSubjects--Topical Terms:

384498
Machine learning
--Congresses.

LC Class. No.: R859.7.A78

Dewey Class. No.: 610.285631

Machine learning applications in medicine and biology
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520 $a 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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