{"product_id":"signal-processing-in-medicine-and-biology-innovations-in-big-data-processing-9783031212352","title":"Signal Processing in Medicine and Biology: Innovations in Big Data Processing","description":"\u003cp\u003e\u003c\/p\u003e\u003cblockquote\u003e\n\u003cbr\u003eSignal Processing in Medicine and Biology: Innovations in Big Data Processing is a book that explores state-of-the-art innovations in biomedical signal processing, focusing on large data sets and machine learning. It offers tutorials, examples, and implementation specifics for professionals, researchers, and students interested in applications in healthcare, engineering, and computer science. \u003c\/blockquote\u003e\u003cp\u003e\u003cstrong\u003eFormat\u003c\/strong\u003e: Hardback\u003cbr\u003e\u003cstrong\u003eLength\u003c\/strong\u003e: 150 pages\u003cbr\u003e\u003cstrong\u003ePublication date\u003c\/strong\u003e: 10 February 2023\u003cbr\u003e\u003cstrong\u003ePublisher\u003c\/strong\u003e: Springer International Publishing AG\u003cbr\u003e\u003c\/p\u003e \u003cp\u003e\u003cbr\u003eSignal Processing in Medicine and Biology: Innovations in Big Data Processing delves into the forefront of interdisciplinary advancements in biomedical signal processing, particularly in the context of handling large data sets and leveraging machine learning techniques. This comprehensive book offers a detailed exploration of cutting-edge solutions, accompanied by comprehensive mathematics and precise implementation details, empowering readers to master these techniques with utmost proficiency. Presented in a tutorial-style format, the book showcases successful applications and appeals to a diverse audience, including professionals, researchers, and students passionate about the intersection of healthcare, engineering, and computer science.\u003cbr\u003e\u003cbr\u003eThe field of signal processing in medicine and biology has witnessed remarkable advancements in recent years, driven by the rapid growth of big data and the emergence of powerful computing technologies. This book aims to provide a comprehensive and interdisciplinary perspective on the latest innovations in biomedical signal processing, particularly focusing on their applications in handling large data sets and leveraging machine learning algorithms.\u003cbr\u003e\u003cbr\u003eChapter 1: Introduction to Biomedical Signal Processing\u003cbr\u003e\u003cbr\u003eIn this chapter, the authors provide an overview of the field of biomedical signal processing, highlighting its importance in healthcare and biology. They discuss the various types of signals encountered in medical imaging, electrophysiology, and genetics, and the challenges associated with processing and analyzing these data. The chapter also introduces the basic concepts and principles of signal processing, including Fourier analysis, linear algebra, and probability theory.\u003cbr\u003e\u003cbr\u003eChapter 2: Large Data Processing in Biomedical Signal Processing\u003cbr\u003e\u003cbr\u003eChapter 2 delves into the challenges of processing large data sets in biomedical signal processing. The authors discuss the importance of data compression, storage, and retrieval, as well as the use of distributed computing frameworks to efficiently handle large datasets. They also introduce the concept of data mining and machine learning, which play crucial roles in extracting meaningful information from large data sets.\u003cbr\u003e\u003cbr\u003eChapter 3: Machine Learning in Biomedical Signal Processing\u003cbr\u003e\u003cbr\u003eChapter 3 explores the application of machine learning in biomedical signal processing. The authors discuss the various supervised and unsupervised learning algorithms, including regression, classification, and clustering. They also introduce the concept of deep learning, which has revolutionized the field by enabling the analysis of complex data patterns. The chapter provides examples of successful applications of machine learning in medical imaging, electrophysiology, and genetics.\u003cbr\u003e\u003cbr\u003eChapter 4: Applications of Biomedical Signal Processing\u003cbr\u003e\u003cbr\u003eChapter 4 showcases successful applications of biomedical signal processing in various healthcare and biology domains. The authors discuss the use of signal processing in medical imaging, such as MRI, CT, and ultrasound, for diagnosing and monitoring diseases. They also discuss the use of signal processing in electrophysiology, such as EEG and ECG, for studying brain activity and diagnosing neurological disorders. Finally, they discuss the use of signal processing in genetics, such as DNA sequencing and genotyping, for identifying genetic mutations and predicting disease risk.\u003cbr\u003e\u003cbr\u003eChapter 5: Conclusion and Future Directions\u003cbr\u003e\u003cbr\u003eIn the conclusion, the authors summarize the key findings and advancements in biomedical signal processing discussed in the previous chapters. They also provide insights into the future directions of the field, including the development of new algorithms, the integration of artificial intelligence and machine learning, and the application of signal processing in personalized medicine.\u003cbr\u003e\u003cbr\u003eThis book is a valuable resource for professionals, researchers, and students interested in the applications of signal processing in medicine and biology. It provides a comprehensive and interdisciplinary perspective on the latest innovations in biomedical signal processing, enabling readers to gain a deep understanding of the techniques and their practical applications. The detailed mathematics and implementation specifics make the book accessible to a wide range of readers, regardless of their technical background.\u003cbr\u003e\u003cbr\u003eIn conclusion, Signal Processing in Medicine and Biology: Innovations in Big Data Processing offers a comprehensive and interdisciplinary exploration of state-of-the-art innovations in biomedical signal processing, particularly in the context of large data sets and machine learning. By presenting detailed mathematics and comprehensive implementation details, the book empowers readers to master these techniques and apply them to real-world applications in healthcare, engineering, and computer science. The book's tutorial-style format and successful applications make it an invaluable resource for professionals, researchers, and students passionate about the intersection of healthcare, engineering, and computer science.\u003c\/p\u003e\u003cp\u003e\u003cstrong\u003eWeight\u003c\/strong\u003e: 412g\u003cbr\u003e\u003cstrong\u003eDimension\u003c\/strong\u003e: 235 x 155 (mm)\u003cbr\u003e\u003cstrong\u003eISBN-13\u003c\/strong\u003e: 9783031212352\u003cbr\u003e \u003cstrong\u003eEdition number\u003c\/strong\u003e: 1st ed. 2023\u003c\/p\u003e","brand":"Shulph Ink","offers":[{"title":"Hardback","offer_id":44302294515962,"sku":"9783031212352","price":83.29,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0522\/4297\/2845\/products\/noImage_1_649133c2-2386-4ec5-a6b2-1898bf44cd1f.jpg?v=1687924371","url":"https:\/\/shulphink.com\/products\/signal-processing-in-medicine-and-biology-innovations-in-big-data-processing-9783031212352","provider":"Shulph Ink","version":"1.0","type":"link"}