Название: Computational Intelligence and Blockchain in Biomedical and Health Informatics
Автор: Pankaj Bhambri, Sita Rani, Muhammad Fahim
Издательство: CRC Press
Год: 2024
Страниц: 361
Язык: английский
Формат: pdf (true)
Размер: 30.6 MB

Advancements in computational intelligence, which encompasses Artificial Intelligence, Machine Learning, and data analytics, have revolutionized the way we process and analyze biomedical and health data. These techniques offer novel approaches to understanding complex biological systems, improving disease diagnosis, optimizing treatment plans, and enhancing patient outcomes. Computational Intelligence and Blockchain in Biomedical and Health Informatics introduces the role of computational intelligence and blockchain in the biomedical and health informatics fields and provides a framework and summary of the various methods. The book emphasizes the role of advanced computational techniques and offers demonstrative examples throughout. Techniques to analyze the impacts on the biomedical and health Informatics domains are discussed along with major challenges in deployment. Rounding out the book are highlights of the transformative potential of computational intelligence and blockchain in addressing critical issues in healthcare from disease diagnosis and personalized medicine to health data management and interoperability along with two case studies. This book is highly beneficial to educators, researchers, and anyone involved with health data.

Machine Learning, on the other hand, takes advantage of methods that allow computers to discover patterns and make predictions without being explicitly programmed to do so. Models are trained using labelled data in supervised learning, while unlabelled data is used in unsupervised learning. Decision trees, support vector machines, and neural networks are all examples of common Machine Learning methods. Data-driven decision-making is essential in many fields, including healthcare, finance, and technology, and both statistical and Machine Learning approaches play important roles in this process. The statistical approaches’ rigor in inference and interpretation is complemented by the versatility of Machine Learning in processing high-dimensional data for applications like image recognition and NLP. Integrating these methods furthers the development of AI and data science by improving our capacity to analyze and draw conclusions from a wide variety of information.

Features:

• Introduces the role of computational intelligence and blockchain in the biomedical and health informatics fields.
• Provides a framework and a summary of various computational intelligence and blockchain methods.
• Emphasizes the role of advanced computational techniques and offers demonstrative examples throughout.
• Techniques to analyze the impact on biomedical and health informatics are discussed along with major challenges in deployment.
• Highlights the transformative potential of computational intelligence and blockchain in addressing critical issues in healthcare from disease diagnosis and personalized medicine to health data management and interoperability.