Advances In Artificial Systems For Medicine And Education V
Download Advances In Artificial Systems For Medicine And Education V full books in PDF, epub, and Kindle. Read online free Advances In Artificial Systems For Medicine And Education V ebook anywhere anytime directly on your device. Fast Download speed and no annoying ads. We cannot guarantee that every ebooks is available!
| Author | : Zhengbing Hu |
| Publisher | : Springer Nature |
| Total Pages | : 566 |
| Release | : 2022-01-01 |
| Genre | : Technology & Engineering |
| ISBN | : 3030925374 |
This book broadly covers a scope of the latest advances for the development of artificial intelligence systems and their applications in various fields from medicine and technology to education. The proceedings comprise refereed papers presented at the Fifth International Conference of Artificial Intelligence, Medical Engineering, and Education (AIMEE2021), which took place at the Mechanical Engineering Institute of the Russian Academy of Sciences, Moscow, Russia, on 1–3 October 2021. Given the rapid development of artificial intelligence systems, the book emphasizes the need for the intensification of training of a growing number of relevant specialists, in particular, in medical engineering to increase the effectiveness of medical diagnosing and treatment. In digital artificial intelligence systems, scientists endeavour to reproduce the innate intellectual abilities of humans 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. Topics of the included papers concern thematic materials in the following spheres: mathematics and biomathematics; medical approaches; technological and educational approaches. The book is a compilation of cutting-edge research 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 who are interested in artificial intelligence, bioinformatics systems, also their expanding applications. The intended readership includes specialists, students, and other circles of readers who would like to know where artificial intelligence systems can be applied in the future with great benefit.
| Author | : Zhengbing Hu |
| Publisher | : Springer |
| Total Pages | : 766 |
| Release | : 2019-05-16 |
| Genre | : Technology & Engineering |
| ISBN | : 3030120821 |
This book includes the proceedings of the Second International Conference of Artificial Intelligence, Medical Engineering, Education (AIMEE2018), held in Moscow, Russia, on 6–8 October 2018. The conference covered advances in the development of artificial intelligence systems and their applications in various fields, from medicine and technology to education. The papers presented in the book discuss topics in mathematics and biomathematics; medical approaches; and technological and educational approaches. Given the rapid development of artificial intelligence systems, the book highlights the need for more intensive training for a growing number of specialists, particularly in medical engineering, to increase the effectiveness of medical diagnosis and treatment. The book is intended for specialists, students and other readers who would like to know where artificial intelligence systems can beneficially be applied in the future.
| Author | : Zhengbing Hu |
| Publisher | : Springer Nature |
| Total Pages | : 668 |
| Release | : 2023-01-20 |
| Genre | : Technology & Engineering |
| ISBN | : 3031244680 |
The book provides a thorough overview of recent developments in the design of AI systems and their uses in a range of industries, including education, technology, and bioinformatics. The papers in the proceedings were presented at the Sixth International Conference on Artificial Intelligence, Medical Engineering, and Education (AIMEE2022), which took place in Wuhan, China, from August 19 to 21, 2022. The book underlines the need for the intensification of training of an increasing number of appropriate specialists given the rapid growth of AI systems. In order to replicate human and other species' natural intelligence in digital AI systems, the researchers have been studying genetics and inherited biological processes in-depth. These studies offer fresh ideas for developing ever more powerful AI techniques. The featured articles cover a variety of themes in the fields of mathematics and biomathematics, medical approaches, technical and educational approaches, and medical approaches. The book is a compilation of recent academic papers in the discipline, covering a wide range of topics that are important to both business managers and engineers. This proceedings is a fantastic resource for asset management practitioners, researchers, and academics, as well as undergraduate and graduate students who are interested in AI, bioinformatics systems, and their developing applications. This is due to the breadth and depth of the proceedings. Experts, students, and other people who are interested in learning about how AI systems might be used in the future are the target audience.
| Author | : Zhengbing Hu |
| Publisher | : Springer |
| Total Pages | : 357 |
| Release | : 2017-08-19 |
| Genre | : Technology & Engineering |
| ISBN | : 3319673491 |
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
| Author | : Zhengbing Hu |
| Publisher | : Springer Nature |
| Total Pages | : 414 |
| Release | : 2021-01-29 |
| Genre | : Computers |
| ISBN | : 303067133X |
This book covers the latest advances for the development of artificial intelligence systems and their applications in various fields from medicine and technology to education. The proceedings comprise refereed papers presented at the Fourth International Conference of Artificial Intelligence, Medical Engineering, Education (AIMEE2020), held at the Mechanical Engineering Institute of the Russian Academy of Sciences, Moscow, Russia, in 3–4 October 2020. Given the rapid development of artificial intelligence systems, the book emphasizes the need for the intensification of training of a growing number of relevant specialists, in particular, in medical engineering to increase the effectiveness of medical diagnosing and treatment. 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. Topics of the included papers concern thematic materials in the following spheres: mathematics and biomathematics; medical approaches; 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 is 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. Intended readership includes specialists, students, and other circles of readers who would like to know where artificial intelligence systems can be applied in the future with great benefit.
| Author | : Zhengbing Hu |
| Publisher | : Springer Nature |
| Total Pages | : 497 |
| Release | : 2020-01-14 |
| Genre | : Technology & Engineering |
| ISBN | : 3030391620 |
This book discusses the latest advances in the development of artificial intelligence systems and their applications in various fields, from medicine and technology to education. It comprises papers presented at the Third International Conference of Artificial Intelligence, Medical Engineering, Education (AIMEE2019), held at the Mechanical Engineering Institute of the Russian Academy of Sciences, Moscow, Russia, on 1–3 October 2019. Covering topics such as mathematics and biomathematics; medical approaches; and technological and educational approaches, it is intended for the growing number of specialists and students in this field, as well as other readers interested in discovering where artificial intelligence systems can be applied in the future.
| Author | : Zhengbing Hu |
| Publisher | : Springer |
| Total Pages | : 559 |
| Release | : 2021-12-21 |
| Genre | : Technology & Engineering |
| ISBN | : 9783030925369 |
This book broadly covers a scope of the latest advances for the development of artificial intelligence systems and their applications in various fields from medicine and technology to education. The proceedings comprise refereed papers presented at the Fifth International Conference of Artificial Intelligence, Medical Engineering, and Education (AIMEE2021), which took place at the Mechanical Engineering Institute of the Russian Academy of Sciences, Moscow, Russia, on 1–3 October 2021. Given the rapid development of artificial intelligence systems, the book emphasizes the need for the intensification of training of a growing number of relevant specialists, in particular, in medical engineering to increase the effectiveness of medical diagnosing and treatment. In digital artificial intelligence systems, scientists endeavour to reproduce the innate intellectual abilities of humans 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. Topics of the included papers concern thematic materials in the following spheres: mathematics and biomathematics; medical approaches; technological and educational approaches. The book is a compilation of cutting-edge research 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 who are interested in artificial intelligence, bioinformatics systems, also their expanding applications. The intended readership includes specialists, students, and other circles of readers who would like to know where artificial intelligence systems can be applied in the future with great benefit.
| Author | : Adam Bohr |
| Publisher | : Academic Press |
| Total Pages | : 385 |
| Release | : 2020-06-21 |
| Genre | : Computers |
| ISBN | : 0128184396 |
Artificial Intelligence (AI) in Healthcare is more than a comprehensive introduction to artificial intelligence as a tool in the generation and analysis of healthcare data. The book is split into two sections where the first section describes the current healthcare challenges and the rise of AI in this arena. The ten following chapters are written by specialists in each area, covering the whole healthcare ecosystem. First, the AI applications in drug design and drug development are presented followed by its applications in the field of cancer diagnostics, treatment and medical imaging. Subsequently, the application of AI in medical devices and surgery are covered as well as remote patient monitoring. Finally, the book dives into the topics of security, privacy, information sharing, health insurances and legal aspects of AI in healthcare. - Highlights different data techniques in healthcare data analysis, including machine learning and data mining - Illustrates different applications and challenges across the design, implementation and management of intelligent systems and healthcare data networks - Includes applications and case studies across all areas of AI in healthcare data
| Author | : Tuan D. Pham |
| Publisher | : Springer Nature |
| Total Pages | : 373 |
| Release | : 2021-07-12 |
| Genre | : Science |
| ISBN | : 303069951X |
Artificial intelligence (AI) has become pervasive in most areas of research and applications. While computation can significantly reduce mental efforts for complex problem solving, effective computer algorithms allow continuous improvement of AI tools to handle complexity—in both time and memory requirements—for machine learning in large datasets. Meanwhile, data science is an evolving scientific discipline that strives to overcome the hindrance of traditional skills that are too limited to enable scientific discovery when leveraging research outcomes. Solutions to many problems in medicine and life science, which cannot be answered by these conventional approaches, are urgently needed for society. This edited book attempts to report recent advances in the complementary domains of AI, computation, and data science with applications in medicine and life science. The benefits to the reader are manifold as researchers from similar or different fields can be aware of advanced developments and novel applications that can be useful for either immediate implementations or future scientific pursuit. Features: Considers recent advances in AI, computation, and data science for solving complex problems in medicine, physiology, biology, chemistry, and biochemistry Provides recent developments in three evolving key areas and their complementary combinations: AI, computation, and data science Reports on applications in medicine and physiology, including cancer, neuroscience, and digital pathology Examines applications in life science, including systems biology, biochemistry, and even food technology This unique book, representing research from a team of international contributors, has not only real utility in academia for those in the medical and life sciences communities, but also a much wider readership from industry, science, and other areas of technology and education.
| Author | : David Riaño |
| Publisher | : Springer |
| Total Pages | : 431 |
| Release | : 2019-06-19 |
| Genre | : Computers |
| ISBN | : 303021642X |
This book constitutes the refereed proceedings of the 17th Conference on Artificial Intelligence in Medicine, AIME 2019, held in Poznan, Poland, in June 2019. The 22 revised full and 31 short papers presented were carefully reviewed and selected from 134 submissions. The papers are organized in the following topical sections: deep learning; simulation; knowledge representation; probabilistic models; behavior monitoring; clustering, natural language processing, and decision support; feature selection; image processing; general machine learning; and unsupervised learning.
