Blockchain and Deep Learning for Smart Healthcare (Hardcover)
Akansha Singh
Sold by Grand Eagle Retail, Mason, OH, U.S.A.
AbeBooks Seller since 12 October 2005
New - Hardcover
Condition: New
Quantity: 1 available
Add to basketSold by Grand Eagle Retail, Mason, OH, U.S.A.
AbeBooks Seller since 12 October 2005
Condition: New
Quantity: 1 available
Add to basketHardcover. BLOCKCHAIN and DEEP LEARNING for SMART HEALTHCARE The book discusses the popular use cases and applications of blockchain technology and deep learning in building smart healthcare. The book covers the integration of blockchain technology and deep learning for making smart healthcare systems. Blockchain is used for health record-keeping, clinical trials, patient monitoring, improving safety, displaying information, and transparency. Deep learning is also showing vast potential in the healthcare domain. With the collection of large quantities of patient records and data, and a trend toward personalized treatments. there is a great need for automated and reliable processing and analysis of health information. This book covers the popular use cases and applications of both the above-mentioned technologies in making smart healthcare. Audience Comprises professionals and researchers working in the fields of deep learning, blockchain technology, healthcare & medical informatics. In addition, as the book provides insights into the convergence of deep learning and blockchain technology in healthcare systems and services, medical practitioners as well as healthcare professionals will find this essential reading. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
Seller Inventory # 9781119791744
The book discusses the popular use cases and applications of blockchain technology and deep learning in building smart healthcare.
The book covers the integration of blockchain technology and deep learning for making smart healthcare systems. Blockchain is used for health record-keeping, clinical trials, patient monitoring, improving safety, displaying information, and transparency. Deep learning is also showing vast potential in the healthcare domain. With the collection of large quantities of patient records and data, and a trend toward personalized treatments. there is a great need for automated and reliable processing and analysis of health information. This book covers the popular use cases and applications of both the above-mentioned technologies in making smart healthcare.
Audience
Comprises professionals and researchers working in the fields of deep learning, blockchain technology, healthcare & medical informatics. In addition, as the book provides insights into the convergence of deep learning and blockchain technology in healthcare systems and services, medical practitioners as well as healthcare professionals will find this essential reading.
Akansha Singh, PhD, is an associate professor in the School of Computer Science Engineering and Technology, Bennett University, Greater Noida, India. Dr. Singh has acquired a BTech, MTech, and PhD (IIT Roorkee) in the area of neural networks and remote sensing. She has to her credit more than 70 research papers, 20 books, and numerous conference papers. She has also national and international patents in the field of machine learning. Her area of interest includes mobile computing, artificial intelligence, machine learning, and digital image processing.
Anuradha Dhull, PhD, is an assistant professor in the Department of Computer Science Engineering, The NorthCap University, Gurugram, India. She has published more than 30 research papers in the area of data mining and machine learning. Dr. Anuradha has acquired a BTech, MTech, and PhD in the area of medical diagnosis and machine learning.
Krishna Kant Singh, PhD, is a professor at the Delhi Technical Campus, Greater Noida, India. Dr. Singh has acquired a BTech, MTech, and PhD (IIT Roorkee) in the area of deep learning and remote sensing. He has authored more than 80 technical books and research papers in international conferences and SCIE journals of repute.
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