TY  - GEN
N2  - This book provides an insight into ways of inculcating the need for applying mobile edge data analytics in bioinformatics and medicine. The book is a comprehensive reference that provides an overview of the current state of medical treatments and systems and offers emerging solutions for a more personalized approach to the healthcare field. Topics include deep learning methods for applications in object detection and identification, object tracking, human action recognition, and cross-modal and multimodal data analysis. High performance computing systems for applications in healthcare are also discussed. The contributors also include information on microarray data analysis, sequence analysis, genomics based analytics, disease network analysis, and techniques for big data Analytics and health information technology. Identifies deep learning techniques in mobile edge data analytics and computing environments suitable for applications in healthcare; Introduces big data analytics to the sources available and possible challenges and techniques associated with bioinformatics and the healthcare domain; Features advancements in the computing field to effectively handle and make inferences from voluminous and heterogeneous healthcare data.
DO  - 10.1007/978-3-030-60265-9
DO  - doi
AB  - This book provides an insight into ways of inculcating the need for applying mobile edge data analytics in bioinformatics and medicine. The book is a comprehensive reference that provides an overview of the current state of medical treatments and systems and offers emerging solutions for a more personalized approach to the healthcare field. Topics include deep learning methods for applications in object detection and identification, object tracking, human action recognition, and cross-modal and multimodal data analysis. High performance computing systems for applications in healthcare are also discussed. The contributors also include information on microarray data analysis, sequence analysis, genomics based analytics, disease network analysis, and techniques for big data Analytics and health information technology. Identifies deep learning techniques in mobile edge data analytics and computing environments suitable for applications in healthcare; Introduces big data analytics to the sources available and possible challenges and techniques associated with bioinformatics and the healthcare domain; Features advancements in the computing field to effectively handle and make inferences from voluminous and heterogeneous healthcare data.
T1  - Deep learning and edge computing solutions for high performance computing /
AU  - Suresh, A.,
AU  - Paiva, Sara,
CN  - R859.7.A78
ID  - 1434300
KW  - Medical informatics.
KW  - Machine learning.
KW  - Artificial intelligence
KW  - Edge computing.
KW  - High performance computing.
KW  - Médecine
KW  - Apprentissage automatique.
KW  - Intelligence artificielle en médecine.
KW  - Superinformatique.
SN  - 9783030602659
SN  - 3030602656
TI  - Deep learning and edge computing solutions for high performance computing /
LK  - https://univsouthin.idm.oclc.org/login?url=https://link.springer.com/10.1007/978-3-030-60265-9
UR  - https://univsouthin.idm.oclc.org/login?url=https://link.springer.com/10.1007/978-3-030-60265-9
ER  -