- Published Year: 2018
- Page count: 624
- File Size: 73 Mb
- Language: English
- Published by: Taylor & Francis
- Visited by: 2
- Rating/Review: 4.821879454837779
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ISBN:
9781498773454
1498773451
9781498773461
Signal processing and machine learning for biomedical big data
4.821879454837779
Reviews from our users
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Each download or ask from book AI costs 2 points. To earn more free points, please visit the Points Guide Page and complete some valuable actions.Welcome to the expansive and intricate world of biomedical big data, where the fields of signal processing and machine learning converge to revolutionize the way healthcare systems, diagnostics, and research are conducted. "Signal Processing and Machine Learning for Biomedical Big Data" is your definitive guide on this transformative journey.
Detailed Summary of the Book
In the digital era of healthcare, data is more abundant and intricate than ever before. This book serves as a crucial resource for understanding how to efficiently analyze and interpret the voluminous and complex data sets that define modern biomedical research. It seamlessly integrates concepts from signal processing and machine learning to tackle the unique challenges presented by biomedical big data.
The book begins by establishing a foundation in fundamental concepts, catering to readers ranging from novices to seasoned experts. It covers a wide spectrum of topics, offering a compendium of methodologies and technologies that are currently shaping the future of biomedical sciences. From sophisticated signal analysis techniques to cutting-edge machine learning algorithms, this book prepares readers to engage with and contribute to modern biomedical innovations.
Key Takeaways
- Understand the foundational principles of signal processing and how they apply to biomedical data.
- Learn about various machine learning techniques that are critical for analyzing large datasets.
- Discover practical applications and case studies that highlight the real-world impact of these technologies in medicine.
- Grasp the challenges and ethical considerations when dealing with biomedical big data.
Famous Quotes from the Book
"In the realm of biomedical data, every signal tells a story, and it's the task of signal processing to uncover its narrative."
"Machine learning paves new inroads into personalized medicine, where data-driven insights cater not just to populations, but to individuals."
Why This Book Matters
The convergence of signal processing and machine learning is redefining how we approach healthcare and research. This book is particularly significant as it addresses both the potential and hurdles of leveraging these technologies in a domain where accuracy can be life-saving. As healthcare transitions towards more data-driven models, understanding these tools is paramount for professionals aiming to innovate and improve patient outcomes.
As a comprehensive resource, it fills a vital gap by offering insights that are both theoretically profound and practically applicable. It is designed not only to educate but to inspire and enable healthcare professionals, researchers, and technologists to harness the vast potential of biomedical big data effectively and ethically.
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