Machine Learning Applications in Medicine and Biology

Author:   Ammar Ahmed ,  Joseph Picone
Publisher:   Springer International Publishing AG
Edition:   1st ed. 2024
ISBN:  

9783031518928


Pages:   168
Publication Date:   30 March 2024
Format:   Hardback
Availability:   Manufactured on demand   Availability explained
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Machine Learning Applications in Medicine and Biology


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Author:   Ammar Ahmed ,  Joseph Picone
Publisher:   Springer International Publishing AG
Imprint:   Springer International Publishing AG
Edition:   1st ed. 2024
ISBN:  

9783031518928


ISBN 10:   3031518926
Pages:   168
Publication Date:   30 March 2024
Audience:   Professional and scholarly ,  Professional & Vocational
Format:   Hardback
Publisher's Status:   Active
Availability:   Manufactured on demand   Availability explained
We will order this item for you from a manufactured on demand supplier.

Table of Contents

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

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Author Information

Ammar Ahmed, Ph.D., received his Ph.D. degree from Temple University, USA, in 2021. He is a radar signal processing engineer at Aptiv, Agoura Hills, CA, USA. From 2011 to 2016, Dr. Ahmed served as an electrical engineer for the National Tokamak Fusion Program, where he was responsible for developing an embedded system design of spherical tokamaks. He also spent the summer of 2020 (May-August) as an intern at Qualcomm Technologies, Inc., in San Diego, CA. His research interests are signal processing, data analysis, optimization, and radar systems.  Joseph Picone, Ph.D., received his Ph.D. in Electrical Engineering in 1983 from the Illinois Institute of Technology. He is a professor in the Department of Electrical and Computer Engineering at Temple University. He has spent significant portions of his career in academia (MS State), research (Texas Instruments, AT&T), and the government (NSA). His primary research interests currently are applications of machine learning in the health sciences. Dr. Picone’s research funding sources over the years have included NSF, NIH, DoD, and DARPA as well as the private sector. He has also been involved in several startup companies in healthcare. For over 40 years, his research groups have been known for producing many innovative open-source materials for education and research, including the first state of the art public domain speech recognition system and the TUH EEG Corpus, which has over 8,000 subscribers (see www.isip.piconepress.com). Dr. Picone is a Senior Member of the IEEE, has published extensively in many signal processing-related fields, and holds several patents in human language technology.

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