This book is a detailed reference on biomedical applications using Deep Learning. Because Deep Learning is an important actor shaping the future of Artificial Intelligence, its specific and innovative solutions for both medical and biomedical are very critical. This book provides a recent view of research works on essential, and advanced topics.

The book offers detailed information on the application of Deep Learning for solving biomedical problems. It focuses on different types of data (i.e. raw data, signal-time series, medical images) to enable readers to understand the effectiveness and the potential. It includes topics such as disease diagnosis, image processing perspectives, and even genomics. It takes the reader through different sides of Deep Learning oriented solutions.

The specific and innovative solutions covered in this book for both medical and biomedical applications are critical to scientists, researchers, practitioners, professionals, and educations who are working in the context of the topics.

This book is a detailed reference on biomedical applications using Deep Learning. Because Deep Learning is an important actor shaping the future of Artificial Intelligence, its specific and innovative solutions for both medical and biomedical are very critical. This book provides a recent view of research works on essential, and advanced topics.

The book offers detailed information on the application of Deep Learning for solving biomedical problems. It focuses on different types of data (i.e. raw data, signal-time series, medical images) to enable readers to understand the effectiveness and the potential. It includes topics such as disease diagnosis, image processing perspectives, and even genomics. It takes the reader through different sides of Deep Learning oriented solutions.

The specific and innovative solutions covered in this book for both medical and biomedical applications are critical to scientists, researchers, practitioners, professionals, and educations who are working in the context of the topics.

This book uncovers the stakes and possibilities involved in realising personalised healthcare services through efficient and effective deep learning algorithms, enabling the healthcare industry to develop meaningful and cost-effective services. This requires effective understanding, application and amalgamation of deep learning with several other computing technologies, such as machine learning, data mining, and natural language processing.

This book uncovers the stakes and possibilities involved in realising personalised healthcare services through efficient and effective deep learning algorithms, enabling the healthcare industry to develop meaningful and cost-effective services. This requires effective understanding, application and amalgamation of deep learning with several other computing technologies, such as machine learning, data mining, and natural language processing.

The book covers a wide topic collection starting from essentials of Computational Intelligence to advance, and possible application types against COVID-19 as well as its effects on the field of medical, social, and different data-oriented research scopes. Among these topics, the book also covers very recently, vital topics in terms of fighting against COVID-19 and solutions for future pandemics. The book includes the use of computational intelligence for especially medical diagnosis and treatment, and also data-oriented tracking-predictive solutions, which are key components currently for fighting against COVID-19. In this way, the book will be a key reference work for understanding how computational intelligence and the most recent technologies (i.e. Internet of Healthcare Thing, big data, and data science techniques) can be employed in solution phases and how they change the way of future solutions.

The book also covers research works with negative results so that possibledisadvantages of using computational intelligence solutions and/or experienced side-effects can be known widely for better future of medical solutions and use of intelligent systems against COVID-19 and pandemics. The book is considering both theoretical and applied views to enable readers to be informed about not only research works but also theoretical views about essentials/components of intelligent systems against COVID-19/pandemics, possible modeling scenarios with current and future perspective as well as solution strategies thought by researchers all over the world.

This book is a detailed reference on biomedical applications using Deep Learning. Because Deep Learning is an important actor shaping the future of Artificial Intelligence, its specific and innovative solutions for both medical and biomedical are very critical. This book provides a recent view of research works on essential, and advanced topics.

The book offers detailed information on the application of Deep Learning for solving biomedical problems. It focuses on different types of data (i.e. raw data, signal-time series, medical images) to enable readers to understand the effectiveness and the potential. It includes topics such as disease diagnosis, image processing perspectives, and even genomics. It takes the reader through different sides of Deep Learning oriented solutions.

The specific and innovative solutions covered in this book for both medical and biomedical applications are critical to scientists, researchers, practitioners, professionals, and educations who are working in the context of the topics.

This book is a detailed reference on biomedical applications using Deep Learning. Because Deep Learning is an important actor shaping the future of Artificial Intelligence, its specific and innovative solutions for both medical and biomedical are very critical. This book provides a recent view of research works on essential, and advanced topics.

The book offers detailed information on the application of Deep Learning for solving biomedical problems. It focuses on different types of data (i.e. raw data, signal-time series, medical images) to enable readers to understand the effectiveness and the potential. It includes topics such as disease diagnosis, image processing perspectives, and even genomics. It takes the reader through different sides of Deep Learning oriented solutions.

The specific and innovative solutions covered in this book for both medical and biomedical applications are critical to scientists, researchers, practitioners, professionals, and educations who are working in the context of the topics.

This book uncovers the stakes and possibilities involved in realising personalised healthcare services through efficient and effective deep learning algorithms, enabling the healthcare industry to develop meaningful and cost-effective services. This requires effective understanding, application and amalgamation of deep learning with several other computing technologies, such as machine learning, data mining, and natural language processing.

This book uncovers the stakes and possibilities involved in realising personalised healthcare services through efficient and effective deep learning algorithms, enabling the healthcare industry to develop meaningful and cost-effective services. This requires effective understanding, application and amalgamation of deep learning with several other computing technologies, such as machine learning, data mining, and natural language processing.

The book covers a wide topic collection starting from essentials of Computational Intelligence to advance, and possible application types against COVID-19 as well as its effects on the field of medical, social, and different data-oriented research scopes. Among these topics, the book also covers very recently, vital topics in terms of fighting against COVID-19 and solutions for future pandemics. The book includes the use of computational intelligence for especially medical diagnosis and treatment, and also data-oriented tracking-predictive solutions, which are key components currently for fighting against COVID-19. In this way, the book will be a key reference work for understanding how computational intelligence and the most recent technologies (i.e. Internet of Healthcare Thing, big data, and data science techniques) can be employed in solution phases and how they change the way of future solutions.

The book also covers research works with negative results so that possibledisadvantages of using computational intelligence solutions and/or experienced side-effects can be known widely for better future of medical solutions and use of intelligent systems against COVID-19 and pandemics. The book is considering both theoretical and applied views to enable readers to be informed about not only research works but also theoretical views about essentials/components of intelligent systems against COVID-19/pandemics, possible modeling scenarios with current and future perspective as well as solution strategies thought by researchers all over the world.