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This book presents a systematic evolution of artificial intelligence (AI), its applications, challenges and solutions in the field of healthcare. The book mainly covers the foundations and various methods of learning in artificial intelligence with its application in healthcare industry. This book provides a comprehensive introduction to data analysis using AI as a tool in the generation, normalization and analysis of healthcare data in association with several evaluation techniques and accuracy measurements. The book is divided into three major sections describing the basic foundations of AI…mehr

Produktbeschreibung
This book presents a systematic evolution of artificial intelligence (AI), its applications, challenges and solutions in the field of healthcare. The book mainly covers the foundations and various methods of learning in artificial intelligence with its application in healthcare industry. This book provides a comprehensive introduction to data analysis using AI as a tool in the generation, normalization and analysis of healthcare data in association with several evaluation techniques and accuracy measurements. The book is divided into three major sections describing the basic foundations of AI and its associated algorithms, history of artificial intelligence in healthcare, recent developments and several modeling techniques for the same. The last section of the book provides insights into several implementations and methods of evaluation and accuracy prediction for healthcare analysis in AI. Extensive use of data for analysis and prediction using several technologies has transformed thelives of normal people indirectly effecting our process to communicate, learn, work and socialize within the society. Thus, the book also provides an insight into the ethics of AI that is very vital in the process of implementation and evaluation of healthcare data. The book provides an organized analysis to a considerable part of data in a digitized society. In view of this, it covers the theory, methodology, perfection and verification of empirical work for health-related data processing. Particular attention is devoted to in-depth experiments and applications.
Autorenporträt
Dr. Jyotismita Talukdar is presently working as Assistant Professor in the dept. Of Computer Science and Engineering at Tezpur University,  Assam, India. She has been actively associated in teaching and several research areas such as data science and machine learning algorithms. She obtained her Ph.D. in 2018 from Gauhati University, Assam, and master's from Asian Institute of Technology, Thailand in 2013. She carries  9 years of teaching experience and has authored a large number of research papers and several books. Dr. Thipendra. P. Singhis currently working as Professor at School of Computer Science Engineering & Technology, Bennett University, Greater Noida, India. He holds Doctorate in Computer Science from Jamia Millia Islamia University, New Delhi, and carries 27 years of teaching and industry experience. Dr. Singh is a senior member of IEEE and member of various other professional bodies including IEI, ACM, EAI, ISTE, IAENG etc. He has been editor of 10 books on various allied topics of Computer Science and published around 50 research papers in high quality journals. Mr. Basanta Barman is currently working as System Administrator at Assam Science and Technology University,Assam,India. Prior to this, he has 11 years of  experience in TCS performing various roles as Database  Administrator, Data Analyst, IT/System Analyst, etc. An Oracle Certified Associate who worked with various projects of different regions like India, South Africa and Canada, he is very keen in upcoming new technologies.