eBook, PDF

Machine Learning Applications in Medicine and Biology (eBook, PDF)

Beschreibung

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.

Technische Details

• Geräte: PC
• ohne Kopierschutz
• Größe: 7.3MB

Barrierefreiheit

• Text-to-Speech
• E-Mail des Verlags für Barrierefreiheitsfragen: [e-mail]
• Alle Inhalte über Screenreader oder taktile Geräte zugänglich
• Navigation über vor-/zurück-Elemente ohne Inhaltsverzeichnis
• Hoher Kontrast zwischen Text und Hintergrund (min. 4.5 =>1)
• Inhalte verständlich ohne Farbwahrnehmung
• Kurze Alternativtexte für nicht-textuelle Inhalte vorhanden
• Text und Medien in logischer Lesereihenfolge angeordnet
• Navigierbares Inhaltsverzeichnis für direkten Zugriff auf Text und Medien
• Keine Einschränkung der Vorlesefunktionen, außer bei spezifischen Ausnahmen

Autor

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.

Produktdetails

• Verlag: Springer International Publishing
• Seitenzahl: 168
• Erscheinungstermin: 29. März 2024
• Englisch
• ISBN-13: 9783031518935
• Artikelnr.: 70264753