
Machine Learning and Deep Learning in Efficacy Improvement of Healthcare Systems
Description
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FEATURES
Explores different dimensions of computational intelligence applications and illustrates its use in the solution of assorted real-world biomedical and healthcare problems
Provides guidance in developing intelligence-based diagnostic systems, efficient models and cost-effective machines
Provides the latest research findings, solutions to the concerning issues and relevant theoretical frameworks in the area of machine learning and deep learning for healthcare systems
Describes experiences and findings relating to protocol design, prototyping, experimental evaluation, real testbeds and empirical characterization of security and privacy interoperability issues in healthcare applications
Explores and illustrates the current and future impacts of pandemics and mitigates risk in healthcare with advanced analytics
This book is intended for students, researchers, professionals and policy makers working in the fields of public health and in the healthcare sector. Scientists and IT specialists will also find this book beneficial for research exposure and new ideas in the field of machine learning and deep learning.
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Persons
Dr. Bharat Bhushan is an Assistant Professor of Department of Computer Science and Engineering (CSE) at School of Engineering and Technology, Sharda University, Greater Noida, India.
Dr. Nitin Rakesh is the Head of Computer Science & Engineering Department for B.Tech/M.Tech (CSE/IT), B.Tech CSE-IBM Specializations, B.Tech CSE-I Nurture, BCA/MCA, BSc/MSc-CS at School of Engineering and Technology,at Sharda University, India.
Dr. Parma Nand is a Dean, School of Engineering Technology, Sharda University Greater Noida.
Dr. Yousef Farhaoui is a Professor at Moulay Ismail University, Faculty of Sciences and Techniques, Morocco.
Content
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