Introduction to Biomedical Data Science PDF Download

Author: Robert Hoyt
Publisher: Lulu.com
ISBN: 179476173X
Category : Science
Languages : en
Pages : 260

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Book Description
Overview of biomedical data science -- Spreadsheet tools and tips -- Biostatistics primer -- Data visualization -- Introduction to databases -- Big data -- Bioinformatics and precision medicine -- Programming languages for data analysis -- Machine learning -- Artificial intelligence -- Biomedical data science resources -- Appendix A: Glossary -- Appendix B: Using data.world -- Appendix C: Chapter exercises.

Author: Sarah J. Pitt
Publisher: John Wiley & Sons
ISBN: 111868771X
Category : Science
Languages : en
Pages : 241

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Book Description
Biomedical Science in Professional and Clinical Practice is essential reading for all trainee biomedical scientists looking for an introduction to the biomedical science profession whether they are undergraduates following an accredited biomedical sciences BSc, graduate trainees or experienced staff with overseas qualifications. This book guides trainees through the subjects, which they need to understand to meet the standards required by the Health Professions Council for state registration. These include professional topics, laws and guidelines governing clinical pathology, basic laboratory techniques and an overview of each pathology discipline. It helps trainees at any stage of training and in any pathology discipline(s) to think creatively about how to gather evidence of their understanding and professional competence. By referring to specialist sources of information in each area, it helps students to explore particular topics in more depth and to keep up to date with professional and legal changes. It is also of value to any Training Officers who are looking for ideas while planning a programme of training for a trainee biomedical scientist. The book includes basic principles of working in the pathology laboratory including laws and regulations, which must be observed, such as health and safety, data protection and equal opportunities laws and guidelines. Practical exercises are included throughout the book with examples of coursework, suggestions for further exercises and self -assessment. Summary boxes of key facts are clearly set out in each chapter and ideas for group/tutorial discussions are also provided to enhance student understanding.

Author: Rafael A. Irizarry
Publisher: CRC Press
ISBN: 1498775861
Category : Mathematics
Languages : en
Pages : 461

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Book Description
This book covers several of the statistical concepts and data analytic skills needed to succeed in data-driven life science research. The authors proceed from relatively basic concepts related to computed p-values to advanced topics related to analyzing highthroughput data. They include the R code that performs this analysis and connect the lines of code to the statistical and mathematical concepts explained.

Author: Khalid Al-Jabery
Publisher: Academic Press
ISBN: 0128144831
Category : Technology & Engineering
Languages : en
Pages : 312

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Book Description
Computational Learning Approaches to Data Analytics in Biomedical Applications provides a unified framework for biomedical data analysis using varied machine learning and statistical techniques. It presents insights on biomedical data processing, innovative clustering algorithms and techniques, and connections between statistical analysis and clustering. The book introduces and discusses the major problems relating to data analytics, provides a review of influential and state-of-the-art learning algorithms for biomedical applications, reviews cluster validity indices and how to select the appropriate index, and includes an overview of statistical methods that can be applied to increase confidence in the clustering framework and analysis of the results obtained. Includes an overview of data analytics in biomedical applications and current challenges Updates on the latest research in supervised learning algorithms and applications, clustering algorithms and cluster validation indices Provides complete coverage of computational and statistical analysis tools for biomedical data analysis Presents hands-on training on the use of Python libraries, MATLAB® tools, WEKA, SAP-HANA and R/Bioconductor

Author: Michael Insana
Publisher: Cambridge University Press
ISBN: 1316832767
Category : Technology & Engineering
Languages : en
Pages : 405

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Book Description
Discover the fundamental principles of biomedical measurement design and performance evaluation with this hands-on guide. Whether you develop measurement instruments or use them in novel ways, this practical text will prepare you to be an effective generator and consumer of biomedical data. Designed for both classroom instruction and self-study, it explains how information is encoded into recorded data and can be extracted and displayed in an accessible manner. Describes and integrates experimental design, performance assessment, classification, and system modelling. Combines mathematical concepts with computational models, providing the tools needed to answer advanced biomedical questions. Includes MATLAB® scripts throughout to help readers model all types of biomedical systems, and contains numerous homework problems, with a solutions manual available online. This is an essential text for advanced undergraduate and graduate students in bioengineering, electrical and computer engineering, computer science, medical physics, and anyone preparing for a career in biomedical sciences and engineering.

Author: John Enderle
Publisher: Elsevier
ISBN: 0080473148
Category : Science
Languages : en
Pages : 1144

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Book Description
Under the direction of John Enderle, Susan Blanchard and Joe Bronzino, leaders in the field have contributed chapters on the most relevant subjects for biomedical engineering students. These chapters coincide with courses offered in all biomedical engineering programs so that it can be used at different levels for a variety of courses of this evolving field. Introduction to Biomedical Engineering, Second Edition provides a historical perspective of the major developments in the biomedical field. Also contained within are the fundamental principles underlying biomedical engineering design, analysis, and modeling procedures. The numerous examples, drill problems and exercises are used to reinforce concepts and develop problem-solving skills making this book an invaluable tool for all biomedical students and engineers. New to this edition: Computational Biology, Medical Imaging, Genomics and Bioinformatics. * 60% update from first edition to reflect the developing field of biomedical engineering * New chapters on Computational Biology, Medical Imaging, Genomics, and Bioinformatics * Companion site: http://intro-bme-book.bme.uconn.edu/ * MATLAB and SIMULINK software used throughout to model and simulate dynamic systems * Numerous self-study homework problems and thorough cross-referencing for easy use

Author: Gareth James
Publisher: Springer Nature
ISBN: 3031387473
Category : Mathematics
Languages : en
Pages : 617

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Book Description
An Introduction to Statistical Learning provides an accessible overview of the field of statistical learning, an essential toolset for making sense of the vast and complex data sets that have emerged in fields ranging from biology to finance, marketing, and astrophysics in the past twenty years. This book presents some of the most important modeling and prediction techniques, along with relevant applications. Topics include linear regression, classification, resampling methods, shrinkage approaches, tree-based methods, support vector machines, clustering, deep learning, survival analysis, multiple testing, and more. Color graphics and real-world examples are used to illustrate the methods presented. This book is targeted at statisticians and non-statisticians alike, who wish to use cutting-edge statistical learning techniques to analyze their data. Four of the authors co-wrote An Introduction to Statistical Learning, With Applications in R (ISLR), which has become a mainstay of undergraduate and graduate classrooms worldwide, as well as an important reference book for data scientists. One of the keys to its success was that each chapter contains a tutorial on implementing the analyses and methods presented in the R scientific computing environment. However, in recent years Python has become a popular language for data science, and there has been increasing demand for a Python-based alternative to ISLR. Hence, this book (ISLP) covers the same materials as ISLR but with labs implemented in Python. These labs will be useful both for Python novices, as well as experienced users.

Author: Laurence J. Street
Publisher: CRC Press
ISBN: 1498722784
Category : Medical
Languages : en
Pages : 527

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Book Description
This new edition provides major revisions to a text that is suitable for the introduction to biomedical engineering technology course offered in a number of technical institutes and colleges in Canada and the US. Each chapter has been thoroughly updated with new photos and illustrations which depict the most modern equipment available in medical technology. This third edition includes new problem sets and examples, detailed block diagrams and schematics and new chapters on device technologies and information technology.

Author: Joseph DuBovy
Publisher: Gregg Division McGraw-Hill
ISBN:
Category : Medical
Languages : en
Pages : 408

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Book Description
This book discusses a basic exploration of the biomedical frequency spectrum and its physiochemical origins, and how physiological data are changed into electric signals or amplified.

Author: Jay A. Etchings
Publisher: John Wiley & Sons
ISBN: 1119256186
Category : Medical
Languages : en
Pages : 464

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Book Description
An essential guide to healthcare data problems, sources, and solutions Strategies in Biomedical Data Science provides medical professionals with much-needed guidance toward managing the increasing deluge of healthcare data. Beginning with a look at our current top-down methodologies, this book demonstrates the ways in which both technological development and more effective use of current resources can better serve both patient and payer. The discussion explores the aggregation of disparate data sources, current analytics and toolsets, the growing necessity of smart bioinformatics, and more as data science and biomedical science grow increasingly intertwined. You'll dig into the unknown challenges that come along with every advance, and explore the ways in which healthcare data management and technology will inform medicine, politics, and research in the not-so-distant future. Real-world use cases and clear examples are featured throughout, and coverage of data sources, problems, and potential mitigations provides necessary insight for forward-looking healthcare professionals. Big Data has been a topic of discussion for some time, with much attention focused on problems and management issues surrounding truly staggering amounts of data. This book offers a lifeline through the tsunami of healthcare data, to help the medical community turn their data management problem into a solution. Consider the data challenges personalized medicine entails Explore the available advanced analytic resources and tools Learn how bioinformatics as a service is quickly becoming reality Examine the future of IOT and the deluge of personal device data The sheer amount of healthcare data being generated will only increase as both biomedical research and clinical practice trend toward individualized, patient-specific care. Strategies in Biomedical Data Science provides expert insight into the kind of robust data management that is becoming increasingly critical as healthcare evolves.