Advances in artificial systems for medicine and education

Advances in artificial systems for medicine and education

Author
He, MatthewHu, ZhengbingPetoukhov, Sergey
Language
English
Year
2018
Page
xiii, 344 Seiten : Illustrationen
ISBN
9783319673486,9783319673493,3319673483
File Type
pdf
File Size
13.9 MiB

This book presents an overview of the latest artificial intelligence systems and methods, which have a broad spectrum of effective and sometimes unexpected applications in medical, educational and other fields of sciences and technology. In digital artificial intelligence systems, scientists endeavor to reproduce the innate intellectual abilities of human and other organisms, and the in-depth study of genetic systems and inherited biological processes can provide new approaches to create more and more effective artificial intelligence methods. The book focuses on the intensive development of bio-mathematical studies on living organism patents, which ensure the noise immunity of genetic information, its quasi-holographic features, and its connection with the Boolean algebra of logic used in technical artificial intelligence systems. In other words, the study of genetic systems and creation of methods of artificial intelligence go hand in hand, mutually enriching enrich each other.

These proceedings comprise refereed papers presented at the 1st International Conference of Artificial Intelligence, Medical Engineering, and Education (AIMEE2017), held at the Mechanical Engineering Institute of the Russian Academy of Sciences, Moscow, Russia on 21–23 August 2017. The topics discussed include advances in thematic mathematics and bio-mathematics; advances in thematica medical approaches; and advances in thematic technological and educational approaches.

The book is a compilation of state-of-the-art papers in the field, covering a comprehensive range of subjects that are relevant to business managers and engineering professionals alike. The breadth and depth of these proceedings make them an excellent resource for asset management practitioners, researchers and academics, as well as undergraduate and postgraduate students interested in artificial intelligence and bioinformatics systems as well as their growing applications

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