Analyzing the Large Number of Variables in Biomedical and Satellite Imagery
Analyzing the Large Number of Variables in Biomedical and Satellite Imagery

Author: Phillip I. Good

Publisher: John Wiley & Sons

Published: 2011-05-18

Total Pages: 169

ISBN-13: 1118002148

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This book grew out of an online interactive offered through statcourse.com, and it soon became apparent to the author that the course was too limited in terms of time and length in light of the broad backgrounds of the enrolled students. The statisticians who took the course needed to be brought up to speed both on the biological context as well as on the specialized statistical methods needed to handle large arrays. Biologists and physicians, even though fully knowledgeable concerning the procedures used to generate microaarrays, EEGs, or MRIs, needed a full introduction to the resampling methods—the bootstrap, decision trees, and permutation tests, before the specialized methods applicable to large arrays could be introduced. As the intended audience for this book consists both of statisticians and of medical and biological research workers as well as all those research workers who make use of satellite imagery including agronomists and meteorologists, the book provides a step-by-step approach to not only the specialized methods needed to analyze the data from microarrays and images, but also to the resampling methods, step-down multi-comparison procedures, multivariate analysis, as well as data collection and pre-processing. While many alternate techniques for analysis have been introduced in the past decade, the author has selected only those techniques for which software is available along with a list of the available links from which the software may be purchased or downloaded without charge. Topical coverage includes: very large arrays; permutation tests; applying permutation tests; gathering and preparing data for analysis; multiple tests; bootstrap; applying the bootstrap; classification methods; decision trees; and applying decision trees.

Analyzing the Large Number of Variables in Biomedical and Satellite Imagery
Analyzing the Large Number of Variables in Biomedical and Satellite Imagery

Author: Phillip I. Good

Publisher: John Wiley & Sons

Published: 2011-05-03

Total Pages: 0

ISBN-13: 0470927143

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This book grew out of an online interactive offered through statcourse.com, and it soon became apparent to the author that the course was too limited in terms of time and length in light of the broad backgrounds of the enrolled students. The statisticians who took the course needed to be brought up to speed both on the biological context as well as on the specialized statistical methods needed to handle large arrays. Biologists and physicians, even though fully knowledgeable concerning the procedures used to generate microaarrays, EEGs, or MRIs, needed a full introduction to the resampling methods—the bootstrap, decision trees, and permutation tests, before the specialized methods applicable to large arrays could be introduced. As the intended audience for this book consists both of statisticians and of medical and biological research workers as well as all those research workers who make use of satellite imagery including agronomists and meteorologists, the book provides a step-by-step approach to not only the specialized methods needed to analyze the data from microarrays and images, but also to the resampling methods, step-down multi-comparison procedures, multivariate analysis, as well as data collection and pre-processing. While many alternate techniques for analysis have been introduced in the past decade, the author has selected only those techniques for which software is available along with a list of the available links from which the software may be purchased or downloaded without charge. Topical coverage includes: very large arrays; permutation tests; applying permutation tests; gathering and preparing data for analysis; multiple tests; bootstrap; applying the bootstrap; classification methods; decision trees; and applying decision trees.

Theoretical and Methodological Approaches to Social Sciences and Knowledge Management
Theoretical and Methodological Approaches to Social Sciences and Knowledge Management

Author: Asunción Lopez-Varela Azcárate

Publisher: BoD – Books on Demand

Published: 2012-08-16

Total Pages: 424

ISBN-13: 9535106872

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This is a unique and groundbreaking collection of questions and answers coming from higher education institutions on diverse fields and across a wide spectrum of countries and cultures. It creates routes for further innovation, collaboration amidst the Sciences (both Natural and Social), the Humanities, and the private and public sectors of society. The chapters speak across sociocultural concerns, education, welfare and artistic sectors under the common desire for direct responses in more effective ways by means of interaction across societal structures.

E-Health and Telemedicine: Concepts, Methodologies, Tools, and Applications
E-Health and Telemedicine: Concepts, Methodologies, Tools, and Applications

Author: Management Association, Information Resources

Publisher: IGI Global

Published: 2015-09-23

Total Pages: 1798

ISBN-13: 1466687576

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Advances in medical technology increase both the efficacy and efficiency of medical practice, and mobile technologies enable modern doctors and nurses to treat patients remotely from anywhere in the world. This technology raises issues of quality of care and medical ethics, which must be addressed. E-Health and Telemedicine: Concepts, Methodologies, Tools, and Applications explores recent advances in mobile medicine and how this technology impacts modern medical care. Three volumes of comprehensive coverage on crucial topics in wireless technologies for enhanced medical care make this multi-volume publication a critical reference source for doctors, nurse practitioners, hospital administrators, and researchers and academics in all areas of the medical field. This seminal publication features comprehensive chapters on all aspects of e-health and telemedicine, including implementation strategies; use cases in cardiology, infectious diseases, and cytology, among others; care of individuals with autism spectrum disorders; and medical image analysis.

Biomedical Texture Analysis
Biomedical Texture Analysis

Author: Adrien Depeursinge

Publisher: Academic Press

Published: 2017-08-25

Total Pages: 432

ISBN-13: 0128123214

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Biomedical Texture Analysis: Fundamentals, Applications, Tools and Challenges describes the fundamentals and applications of biomedical texture analysis (BTA) for precision medicine. It defines what biomedical textures (BTs) are and why they require specific image analysis design approaches when compared to more classical computer vision applications. The fundamental properties of BTs are given to highlight key aspects of texture operator design, providing a foundation for biomedical engineers to build the next generation of biomedical texture operators. Examples of novel texture operators are described and their ability to characterize BTs are demonstrated in a variety of applications in radiology and digital histopathology. Recent open-source software frameworks which enable the extraction, exploration and analysis of 2D and 3D texture-based imaging biomarkers are also presented. This book provides a thorough background on texture analysis for graduate students and biomedical engineers from both industry and academia who have basic image processing knowledge. Medical doctors and biologists with no background in image processing will also find available methods and software tools for analyzing textures in medical images. - Defines biomedical texture precisely and describe how it is different from general texture information considered in computer vision - Defines the general problem to translate 2D and 3D texture patterns from biomedical images to visually and biologically relevant measurements - Describes, using intuitive concepts, how the most popular biomedical texture analysis approaches (e.g., gray-level matrices, fractals, wavelets, deep convolutional neural networks) work, what they have in common, and how they are different - Identifies the strengths, weaknesses, and current challenges of existing methods including both handcrafted and learned representations, as well as deep learning. The goal is to establish foundations for building the next generation of biomedical texture operators - Showcases applications where biomedical texture analysis has succeeded and failed - Provides details on existing, freely available texture analysis software, helping experts in medicine or biology develop and test precise research hypothesis

The A-Z of Error-Free Research
The A-Z of Error-Free Research

Author: Phillip I. Good

Publisher: CRC Press

Published: 2012-08-01

Total Pages: 273

ISBN-13: 1439897379

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A Practical Guide with Step-by-Step Explanations, Numerous Worked Examples, and R Code The A–Z of Error-Free Research describes the design, analysis, modeling, and reporting of experiments, clinical trials, and surveys. The book shows you when to use statistics, the best ways to cope with variation, and how to design an experiment, determine optimal sample size, and collect useable data. It also helps you choose the best statistical procedures for your application and takes you step by step through model development and reporting results for publication. Transition from Student to Researcher Helping you become a confident researcher, the book begins with an overview of when—and when not—to use statistics. It guides you through the planning and data collection phases and presents various data analysis techniques, including methods for sample size determination. The author then covers techniques for developing models that provide a basis for future research. He also discusses reporting techniques to ensure your research efforts get the proper credit. The book concludes with case-control and cohort studies.

Information Processing in Medical Imaging
Information Processing in Medical Imaging

Author: Sebastien Ourselin

Publisher: Springer

Published: 2015-06-22

Total Pages: 811

ISBN-13: 3319199927

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This book constitutes the proceedings of the 24th International Conference on Information Processing in Medical Imaging, IPMI 2015, held at the Sabhal Mor Ostaig College on the Isle of Skye, Scotland, UK, in June/July 2015. The 22 full papers and 41 poster papers presented in this volume were carefully reviewed and selected from 195 submissions. They were organized in topical sections named: probabilistic graphical models; MRI reconstruction; clustering; statistical methods; longitudinal analysis; microstructure imaging; shape analysis; multi-atlas fusion; fast image registration; deformation models; and the poster session.

Prostate Cancer Imaging. Image Analysis and Image-Guided Interventions
Prostate Cancer Imaging. Image Analysis and Image-Guided Interventions

Author: Anant Madabhushi

Publisher: Springer

Published: 2011-09-25

Total Pages: 168

ISBN-13: 3642239447

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This book constitutes the refereed proceedings of the International Workshop on Prostate Cancer Imaging, held in conjunction with MICCAI 2011, in Toronto, Canada, in September 2011. The 15 revised full papers presented together with 2 invited talks were carefully reviewed and selected from 19 submissions. The papers cover the clinical areas of radiology, radiation oncology, and image guided intervention, addressing topics such as prostate segmentation, multi-modal prostate registration, and computer-aided diagnosis and classification of prostate cancer.

Artificial Intelligence in Healthcare
Artificial Intelligence in Healthcare

Author: Adam Bohr

Publisher: Academic Press

Published: 2020-06-21

Total Pages: 385

ISBN-13: 0128184396

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Artificial Intelligence (AI) in Healthcare is more than a comprehensive introduction to artificial intelligence as a tool in the generation and analysis of healthcare data. The book is split into two sections where the first section describes the current healthcare challenges and the rise of AI in this arena. The ten following chapters are written by specialists in each area, covering the whole healthcare ecosystem. First, the AI applications in drug design and drug development are presented followed by its applications in the field of cancer diagnostics, treatment and medical imaging. Subsequently, the application of AI in medical devices and surgery are covered as well as remote patient monitoring. Finally, the book dives into the topics of security, privacy, information sharing, health insurances and legal aspects of AI in healthcare. - Highlights different data techniques in healthcare data analysis, including machine learning and data mining - Illustrates different applications and challenges across the design, implementation and management of intelligent systems and healthcare data networks - Includes applications and case studies across all areas of AI in healthcare data

Systems Analytics and Integration of Big Omics Data
Systems Analytics and Integration of Big Omics Data

Author: Gary Hardiman

Publisher: MDPI

Published: 2020-04-15

Total Pages: 202

ISBN-13: 3039287443

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A “genotype" is essentially an organism's full hereditary information which is obtained from its parents. A "phenotype" is an organism's actual observed physical and behavioral properties. These may include traits such as morphology, size, height, eye color, metabolism, etc. One of the pressing challenges in computational and systems biology is genotype-to-phenotype prediction. This is challenging given the amount of data generated by modern Omics technologies. This “Big Data” is so large and complex that traditional data processing applications are not up to the task. Challenges arise in collection, analysis, mining, sharing, transfer, visualization, archiving, and integration of these data. In this Special Issue, there is a focus on the systems-level analysis of Omics data, recent developments in gene ontology annotation, and advances in biological pathways and network biology. The integration of Omics data with clinical and biomedical data using machine learning is explored. This Special Issue covers new methodologies in the context of gene–environment interactions, tissue-specific gene expression, and how external factors or host genetics impact the microbiome.