Computational Intelligence and Its Applications in Healthcare -

Computational Intelligence and Its Applications in Healthcare

Buch | Softcover
264 Seiten
2020
Academic Press Inc (Verlag)
978-0-12-820604-1 (ISBN)
165,85 inkl. MwSt
Computational Intelligence and Its Applications in Healthcare presents rapidly growing applications of computational intelligence for healthcare systems, including intelligent synthetic characters, man-machine interface, menu generators, user acceptance analysis, pictures archiving, and communication systems. Computational intelligence is the study of the design of intelligent agents, which are systems that act intelligently: they do what they think are appropriate for their circumstances and goals; they're flexible to changing environments and goals; they learn from experience; and they make appropriate choices given perceptual limitations and finite computation. Computational intelligence paradigms offer many advantages in maintaining and enhancing the field of healthcare.

Dr. Jitendra Kumar Verma is an Assistant Professor in the School of Computing Science and Engineering, Galgotias University, India. He holds a Ph.D. in Computer Science and Technology from Jawaharlal Nehru University, India. He has been a Visiting Research Scholar at Julius-Maximillian University, Wurzburg, Germany. His research interests include cloud computing, mobile cloud, machine learning, soft computing, fuzzy systems, pattern recognition, bio-inspired phenomena, and advanced optimization models and computation. Dr. Sudip Paul, Post-Doctoral Fellow and PhD, is currently an Associate Professor & Teacher In-Charge in the Department of Biomedical Engineering, School of Technology, North-Eastern Hill University (NEHU), Shillong, India. He has published over 40 journal papers, over 35 conference papers, and has contributed his knowledge as editorial board member and reviewer for multiple international journals. He has been granted one patent of eight filled and completed more than ten book projects. Dr. Sudip has presented his research accomplishments in countries around the world. He is a member of multiple societies and professional bodies, including APSN, ISN, IBRO, SNCI, SfN, IEEE, IAS. Dr. Sudip has received many awards, including the World Federation of Neurology (WFN) traveling fellowship, Young Investigator Award, IBRO Travel Awardee, and ISN Travel Awardee. Dr. Prashant Johri. Professor in School of Computing Science & Engineering, Galgotias University, Greater Noida, India. He completed his B.Sc.(H) in 1992 and M.C.A. in 1992 from A.M.U, Aligarh and Ph.D. in Computer Science from Jiwaji University, Gwalior in 2011, India. He has also worked as a Professor and Director (M.C.A.), Galgotias Institute of Management and Technology and Noida Institute of Engineering and Technology, Gr. Noida. He has served as Chair in many conferences in India and Abroad. He has supervised 2 PhD students and M. Tech. students. He published more than 100 research papers in National and International Journals and Conferences. He has published edited books in Elsevier and Springer. He organized several Conferences / Workshops/Seminars at the national and international levels. His research interest includes Artificial Intelligence, Machine Learning, Data Science, Deep Reinforcement Learning, Information Security, Cloud Computing, Block Chain, Healthcare, Agriculture, Image Processing, Software Reliability.

The impact of Internet of Things and data semantics on decision making for outpatient monitoring
Deep-learning approaches for health care: Patients in intensive care
Brain MRI image segmentation using nature-inspired Black Hole metaheuristic clustering approach
Blockchain for public health: Technology, applications, and a case study
Compression and multiplexing of medical images using optical image processing
Analysis of skin lesions using machine learning techniques
Computational intelligence using ontology—A case study on the knowledge representation in a clinical decision support system
Neural network-based abnormality detection for electrocardiogram time signals
Machine learning approaches for acetic acid test based uterine cervix image analysis
Convolutional neural network for biomedical applications
Alzheimer’s disease classification using deep learning
Diabetic retinopathy identification using autoML
Knowledge-based systems in medical applications
Convolution neural network-based feature learning model for EEG-based driver alert/drowsy state detection
Analysis on the prediction of central line-associated bloodstream infections (CLABSI) using deep neural network classification

Erscheinungsdatum
Verlagsort San Diego
Sprache englisch
Maße 191 x 235 mm
Gewicht 540 g
Themenwelt Informatik Weitere Themen Bioinformatik
Medizin / Pharmazie Physiotherapie / Ergotherapie Orthopädie
Technik Medizintechnik
Technik Umwelttechnik / Biotechnologie
ISBN-10 0-12-820604-7 / 0128206047
ISBN-13 978-0-12-820604-1 / 9780128206041
Zustand Neuware
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