Artículos relacionados a Data Fusion Techniques and Applications for Smart Healthcare...

Data Fusion Techniques and Applications for Smart Healthcare (Intelligent Data-Centric Systems) - Tapa blanda

 
9780443132339: Data Fusion Techniques and Applications for Smart Healthcare (Intelligent Data-Centric Systems)
Tapa blanda
ISBN 10: 044313233X ISBN 13: 9780443132339
Editorial: Academic Press, 2024

Sinopsis

Data Fusion Techniques and Applications for Smart Healthcare covers cutting-edge research from both academia and industry, with a particular emphasis on recent advances in algorithms and applications that involve combining multiple sources of medical information. The book can be used as a reference for practicing engineers, scientists, and researchers, but it will also be useful for graduate students and practitioners from government and industry as well as healthcare technology professionals working on state-of-the-art information fusion solutions for healthcare applications. Medical data exists in several formats, from structured data and medical reports to 1D signals, 2D images, 3D volumes, or even higher dimensional data such as temporal 3D sequences. Healthcare experts can make auscultation reports in text format; electrocardiograms can be printed in time series format, X-rays saved as images; volume can be provided through angiography; temporal information by echocardiograms, and 4D information extracted through flow MRI.

"Sinopsis" puede pertenecer a otra edición de este libro.

Acerca de los autores

Amit Kumar Singh is an associate professor at the Department of Computer Science and Engineering, National Institute of Technology Patna, Bihar, India. Dr. Singh have been recognized as "World Ranking of Top 2% Scientists" in the area of “Biomedical Research" (for Year 2019) and "Artificial Intelligence & Image Processing" (for the Year 2020 and 2021) according to the survey given by Stanford University, USA. Currently, Dr. Singh is the Associate Editor of IEEE Trans. on Multimedia, ACM Trans. Multimedia Comput. Commun. Appl., IEEE Trans. Computat. Social Syst., IEEE Trans. Ind. Informat., IEEE J. Biomed. Heal. Informatics Etc. His research interests include multimedia data hiding, image processing, compression, biometrics, Cryptography.



Prof. Berretti is an associate professor at the Media Integration and Communication Center (MICC) and Department of Information Engineering (DINFO) of the University of Florence (UNIFI), Florence, Italy. In 2017, he obtained habilitation as full professor in Computer Engineering. Prof. Berretti has worked on image databases for effective and efficient image retrieval based on color, shape attributes and spatial relationships. He also investigated the problem of retrieval from repositories distributed on the net using resource selection and results fusion. More recently, his research interests focused on deep learning methods for face recognition, and to their generalization to non-Euclidean domains (i.e., graphs, meshes, manifolds, etc.). He is information director and associate editor of the ACM Transactions on Multimedia Computing, Communication and Applications, and of the IET Computer Vision journal. He is a member of the ACM, and senior member of the IEEE.

De la contraportada

Medical data exists in several formats, from structured data and medical reports to 1D signals, 2D images, 3D volumes, or even higher dimensional data such as temporal 3D sequences. Healthcare experts can make auscultation reports in text format; electrocardiograms can be printed in time series format, x-rays saved as images; volume can be provided through angiography; temporal information by echocardiograms, and 4D information extracted through flow MRI. Another typical source of variability is the existence of data from different time points, such as pre and post treatment, for instance. These large and highly diverse amounts of information need to be organized and mined in an appropriate way so that meaningful information can be extracted. New multimodal data fusion techniques are able to combine salient information into one single source to ensure better diagnostic accuracy and assessment.

Data Fusion Techniques and Applications for Smart Healthcare covers cutting-edge research from both academia and industry with a particular emphasis on recent advances in algorithms and applications that involve combining multiple sources of medical information. This book can be used as a reference for practicing engineers, scientists, and researchers. It will also be useful for graduate students and practitioners from government and industry as well as healthcare technology professionals working on state-of-the-art information fusion solutions for healthcare applications.

"Sobre este título" puede pertenecer a otra edición de este libro.

Editorial
Academic Press
Año de publicación
2024
Idioma
Inglés
ISBN 10 
044313233X
ISBN 13 
9780443132339
Encuadernación
Tapa blanda
Número de páginas
442
Editor
Singh
Contacto del fabricante
no disponible
Persona responsable
Yeepin GmbH
492000000000
sunshine12232@outlook.com

Alleestr.11
Kaiserslautern
Rheinland-Pfalz
67655
Alemania