Название: Applications of Artificial Intelligence in Business, Education and Healthcare
Автор: Allam Hamdan, Aboul Ella Hassanien, Reem Khamis
Издательство: Springer
Год: 2021
Страниц: 502
Язык: английский
Формат: pdf (true), epub
Размер: 20.6 MB

This book focuses on the implementation of Artificial Intelligence in Business, Education and Healthcare, It includes research articles and expository papers on the applications of Artificial Intelligence on Decision Making, Entrepreneurship, Social Media, Healthcare, Education, Public Sector, FinTech, and RegTech. It also discusses the role of Artificial Intelligence in the health sector, education, and others. It also discusses the impact of Artificial Intelligence on decision-making in vital sectors of the economy.

Artificial intelligence is a breakthrough for various felids in life. Endless potential opportunities may be created through applying AI in business, health care, and education. It is undeniable that artificial intelligence provides a cheap and efficient tool to achieve tasks that consume time and money, where faster growth and success could be reached. Transforming into utilizing artificial intelligence needs careful inspection and forward thinking in the possible outcomes and reflections on humankind.

This book contains 26 chapters by authors from different countries. Each of these chapters was evaluated through an editorial board, and each chapter was passed through a double-blind peer review process, hence bestowing four themes:

- Artificial Intelligence, Blockchain Technology, Entrepreneurship, and Business Success.
- FinTech, RegTech, Financial Systems, and Artificial Intelligence.
- Implementation of Artificial Intelligence in Healthcare, Education, and Public Sector.
- Professional Practices and Social Implications of Artificial Intelligence.

Deep reinforcement learning is an active research point in the academic community now more than ever. The computational capabilities and the deep neural networks revolution can automatically find compact low-dimensional features of high-dimensional data. As the convolutional neural network gets better at dealing with the visual world, the more outstanding results show reinforcement-learning agents that can concur with various problems. Intending to develop stronger agents and go beyond the benchmark, we need environments that provide more challenge than the problems that already have solved. Real-time strategy games considered as perfect challenging environment for reinforcement learning agents because of their vast state-action spaces that mimic the state and action spaces in real-world problems. Besides, real-time strategy games are simulations with complicated interactions, so they have no cost when applying trial and error learning techniques. Deep reinforcement learning agents considered a promising step towards fully autonomous agents that learn from trial and error with little or no prior knowledge about the environment they were dealing with.

These chapters reflect quality research contributing theoretical and practical implications for those who wish to apply artificial intelligence within any business, healthcare, education sector, or even entrepreneurs who wish to blend entrepreneurship with artificial intelligence and other vital areas state the lease. We hope that this book’s contribution will be oft the academic level that even decision-makers in the various economic and executive levels will get to appreciate.