Provides a comprehensive overview on the recent developments on clinical decision support systems, precision health and data science in medicine Examines the advancements, challenges and opportunities of using AI in medical and health applications Includes 10 cases for practical application and reference Reviews melanoma detection by deep learning techniques

The availability of molecular imaging and measurement systems enables today's biologists to swiftly monitor thousands of genes involved in a host of diseases, a critical factor in specialized drug development. Systems Biology and Bioinformatics: A Computational Approach provides students with a comprehensive collection of the computational methods used in what is being coined the digital era of biology. Written by field experts with proven track records, this authoritative textbook first provides an introduction to systems biology and its impact on biology and medicine. The book then reviews the basic principles of molecular and cell biology using a system-oriented approach, with a brief description of the high-throughput biological experiments that produce databases. The text includes techniques to discover genes, perform nucleotide and amino acid sequence matching, and estimate static gene dynamic pathways. The book also explains how to use system-oriented models to predict the behavior of biological systems for important applications such as rational drug design. The numerous examples and problem sets allow students to confidently explore practical systems biology applications using real examples with real biological data, making Systems Biology and Bioinformatics: A Computational Approach an ideal text for senior undergraduate and first-year graduate students.

First published in 2005, Biomedical Signal and Image Processing received wide and welcome reception from universities and industry research institutions alike, offering detailed, yet accessible information at the reference, upper undergraduate, and first year graduate level. Retaining all of the quality and precision of the first edition, Biomedical Signal and Image Processing, Second Edition offers a number of revisions and improvements to provide the most up-to-date reference available on the fundamental signal and image processing techniques that are used to process biomedical information. Addressing the application of standard and novel processing techniques to some of today's principle biomedical signals and images over three sections, the book begins with an introduction to digital signal and image processing, including Fourier transform, image filtering, edge detection, and wavelet transform. The second section investigates specifically biomedical signals, such as ECG, EEG, and EMG, while the third focuses on imaging using CT, X-Ray, MRI, ultrasound, positron, and other biomedical imaging techniques. Updated and expanded, Biomedical Signal and Image Processing, Second Edition offers numerous additional, predominantly MATLAB, examples to all chapters to illustrate the concepts described in the text and ensure a complete understanding of the material. The author takes great care to clarify ambiguities in some mathematical equations and to further explain and justify the more complex signal and image processing concepts to offer a complete and understandable approach to complicated concepts.

The availability of molecular imaging and measurement systems enables today's biologists to swiftly monitor thousands of genes involved in a host of diseases, a critical factor in specialized drug development. Systems Biology and Bioinformatics: A Computational Approach provides students with a comprehensive collection of the computational methods used in what is being coined the digital era of biology. Written by field experts with proven track records, this authoritative textbook first provides an introduction to systems biology and its impact on biology and medicine. The book then reviews the basic principles of molecular and cell biology using a system-oriented approach, with a brief description of the high-throughput biological experiments that produce databases. The text includes techniques to discover genes, perform nucleotide and amino acid sequence matching, and estimate static gene dynamic pathways. The book also explains how to use system-oriented models to predict the behavior of biological systems for important applications such as rational drug design. The numerous examples and problem sets allow students to confidently explore practical systems biology applications using real examples with real biological data, making Systems Biology and Bioinformatics: A Computational Approach an ideal text for senior undergraduate and first-year graduate students.