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Author: Linda Miner
Publisher: Academic Press
ISBN: 012411640X
Category : Computers
Languages : en
Pages : 1110
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Book Description
With the advent of electronic medical records years ago and the increasing capabilities of computers, our healthcare systems are sitting on growing mountains of data. Not only does the data grow from patient volume but the type of data we store is also growing exponentially. Practical Predictive Analytics and Decisioning Systems for Medicine provides research tools to analyze these large amounts of data and addresses some of the most pressing issues and challenges where data integrity is compromised: patient safety, patient communication, and patient information. Through the use of predictive analytic models and applications, this book is an invaluable resource to predict more accurate outcomes to help improve quality care in the healthcare and medical industries in the most cost–efficient manner. Practical Predictive Analytics and Decisioning Systems for Medicine provides the basics of predictive analytics for those new to the area and focuses on general philosophy and activities in the healthcare and medical system. It explains why predictive models are important, and how they can be applied to the predictive analysis process in order to solve real industry problems. Researchers need this valuable resource to improve data analysis skills and make more accurate and cost-effective decisions. Includes models and applications of predictive analytics why they are important and how they can be used in healthcare and medical research Provides real world step-by-step tutorials to help beginners understand how the predictive analytic processes works and to successfully do the computations Demonstrates methods to help sort through data to make better observations and allow you to make better predictions
Author: Linda Miner
Publisher: Academic Press
ISBN: 012411640X
Category : Computers
Languages : en
Pages : 1110
Get Book
Book Description
With the advent of electronic medical records years ago and the increasing capabilities of computers, our healthcare systems are sitting on growing mountains of data. Not only does the data grow from patient volume but the type of data we store is also growing exponentially. Practical Predictive Analytics and Decisioning Systems for Medicine provides research tools to analyze these large amounts of data and addresses some of the most pressing issues and challenges where data integrity is compromised: patient safety, patient communication, and patient information. Through the use of predictive analytic models and applications, this book is an invaluable resource to predict more accurate outcomes to help improve quality care in the healthcare and medical industries in the most cost–efficient manner. Practical Predictive Analytics and Decisioning Systems for Medicine provides the basics of predictive analytics for those new to the area and focuses on general philosophy and activities in the healthcare and medical system. It explains why predictive models are important, and how they can be applied to the predictive analysis process in order to solve real industry problems. Researchers need this valuable resource to improve data analysis skills and make more accurate and cost-effective decisions. Includes models and applications of predictive analytics why they are important and how they can be used in healthcare and medical research Provides real world step-by-step tutorials to help beginners understand how the predictive analytic processes works and to successfully do the computations Demonstrates methods to help sort through data to make better observations and allow you to make better predictions
Author: Max Kuhn
Publisher: Springer Science & Business Media
ISBN: 1461468493
Category : Medical
Languages : en
Pages : 600
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Book Description
Applied Predictive Modeling covers the overall predictive modeling process, beginning with the crucial steps of data preprocessing, data splitting and foundations of model tuning. The text then provides intuitive explanations of numerous common and modern regression and classification techniques, always with an emphasis on illustrating and solving real data problems. The text illustrates all parts of the modeling process through many hands-on, real-life examples, and every chapter contains extensive R code for each step of the process. This multi-purpose text can be used as an introduction to predictive models and the overall modeling process, a practitioner’s reference handbook, or as a text for advanced undergraduate or graduate level predictive modeling courses. To that end, each chapter contains problem sets to help solidify the covered concepts and uses data available in the book’s R package. This text is intended for a broad audience as both an introduction to predictive models as well as a guide to applying them. Non-mathematical readers will appreciate the intuitive explanations of the techniques while an emphasis on problem-solving with real data across a wide variety of applications will aid practitioners who wish to extend their expertise. Readers should have knowledge of basic statistical ideas, such as correlation and linear regression analysis. While the text is biased against complex equations, a mathematical background is needed for advanced topics.
Author: Islem Rekik
Publisher: Springer Nature
ISBN: 3030322815
Category : Computers
Languages : en
Pages : 191
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Book Description
This book constitutes the proceedings of the Second International Workshop on Predictive Intelligence in Medicine, PRIME 2019, held in conjunction with MICCAI 2019, in Shenzhen, China, in October 2019. The 18 papers presented in this volume were carefully reviewed and selected for inclusion in this book. The contributions describe new cutting-edge predictive models and methods that solve challenging problems in the medical field for a high-precision predictive medicine.
Author: Emmanuel Fombu
Publisher: Business Expert Press
ISBN: 1951527054
Category : Business & Economics
Languages : en
Pages : 237
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Book Description
Predictive Medicine makes artificial intelligence more accessible for healthcare practitioners without shying away from complex topics and controversial subject matter. Artificial intelligence, machine learning, natural language processing, robotics, big data and other new technologies are ready to revolutionize the way we look at healthcare. But if we want them to achieve their full potential, we’ll need leaders who understand these new tools and who have long-term strategies in place to take advantage of them. This book will help you to become one of those leaders. Predictive Medicine makes artificial intelligence more accessible for healthcare practitioners without shying away from complex topics and controversial subject matter. It’s a call-to-action for a new generation of health leaders and a roadmap to help them usher in a brighter future.
Author: Gabriella Pravettoni
Publisher: Springer Nature
ISBN: 3030279944
Category : Psychology
Languages : en
Pages : 191
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Book Description
This open access volume focuses on the development of a P5 eHealth, or better, a methodological resource for developing the health technologies of the future, based on patients’ personal characteristics and needs as the fundamental guidelines for design. It provides practical guidelines and evidence based examples on how to design, implement, use and elevate new technologies for healthcare to support the management of incurable, chronic conditions. The volume further discusses the criticalities of eHealth, why it is difficult to employ eHealth from an organizational point of view or why patients do not always accept the technology, and how eHealth interventions can be improved in the future. By dealing with the state-of-the-art in eHealth technologies, this volume is of great interest to researchers in the field of physical and mental healthcare, psychologists, stakeholders and policymakers as well as technology developers working in the healthcare sector.
Author: Sunil Badve
Publisher: Springer
ISBN: 3319952285
Category : Medical
Languages : en
Pages : 642
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Book Description
“Precision/personalized or stratified medicine” refers to the tailoring of medical treatment or drug administration to the individual characteristics of each patient treatment. It does not literally mean that a pharmaceutical company makes a drug for an individual patient for consumption and treatment but rather means the ability to stratify (or classify) individuals into sub-populations that differ in their responsiveness to a specific drug. A marker that provides information on the likely response to therapy, i.e., either in terms of tumor shrinkage or survival of the patient is termed “predictive biomarker”. Despite their promise in precision medicine and the explosion of knowledge in this area, there is not a single source on this subject that puts all this evidence together in a concise or richly illustrated and easy to understand manner. This book provides a collection of ingeniously organized, well-illustrated and up-to-date authoritative chapters divided into five sections that are clear and easy to understand. Section one provides an overview of biomarkers, introduces the basic terminologies, definitions, technologies, tools and concepts associated with this subject in the form of illustrations/graphics, photographs and concise texts. Several recent biomarker endeavors that have been initiated and funded by the National Cancer Institute, National Institutes of Health, FDA and other International organizations are presented. Section two involves the signaling pathways controlling cell growth and differentiation altered in cancer. This section analyzes how predictive biomarkers are altered (expressed or amplified) across cancer types. Section three explores how predictive biomarkers play a role in patient stratification and tailored treatment in relationship to specific cancers. In addition, it includes discussion on the various precision medicine initiatives that are going on across the globe (e.g. TARGET, NCI-MATCH, BATTLE, SHIVA, etc.). Section four discusses: (a) how pharmaceutical companies validate predictive biomarker assays and accompanying companion diagnostics either internally or externally with partner companies such as central laboratories or clinical research organizations, and (b) how predictive biomarker tests fall under the oversight of US FDA, Centers for Medicare & Medicaid Services (CMS) and state laws. Section five wraps up novel agents and targets that are being used as targets for cancer therapeutics. The biomarkers associated with these protocols will also be presented. Throughout the book, sidebars, special interest boxes and illustrations are used to explain terms that are either newly introduced, uncommon, or specialized. Predictive Biomarkers in Oncology will serve as a definitive guide for practicing pathologists, oncologists, basic researchers, and personnel in the pharmaceutical or diagnostic industry interested in learning how “predictive biomarkers” are used in precision cancer therapy.
Author: Emanuel Cheraskin
Publisher: Keats Publishing
ISBN: 9780879831509
Category : Medical
Languages : en
Pages : 196
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Book Description
Author: Poonam Tanwar
Publisher: Walter de Gruyter GmbH & Co KG
ISBN: 3110715279
Category : Computers
Languages : en
Pages : 333
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Book Description
This book uncovers stakes and possibilities offered by Computational Intelligence and Predictive Analytics to Medical Science. The main focus is on data technologies,classification, analysis and mining, information retrieval, and in the algorithms needed to elaborate the informations. A section with use cases and applications follows the two main parts of the book, respectively dedicated to the foundations and techniques of the discipline.
Author: Lotfi Chaari
Publisher: Springer Nature
ISBN: 3030498158
Category : Medical
Languages : en
Pages : 164
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Book Description
The edition will cover proceedings of the second International conference on digital health Technologies (ICDHT 2019). The conference will address the topic of P4 medicine from the information technology point of view, and will be focused on the following topics: - Artificial Intelligence for health • Knowledge extraction • Decision-aid systems • Data analysis and risk prediction • Machine learning, deep learning - Health data processing • Data preprocessing, cleaning, management and mining • Computer-aided detection • Big data analysis, prediction and prevention • Cognitive algorithms for healthcare handling dynamic context management • Augmented reality, Motion detection and activity recognition - Devices, infrastructure and communication • Wearable & connected devices • Communication infrastructures, architectures and standards Blockchain for e-Health • Computing/storage infrastructures for e-Health • IoT devices & architectures for Smart Healthcare - Health information systems • Telemedicine, Teleservices • Computing/storage infrastructures for e-Health • Clinical Data Visualisation Standards - Security and privacy for e-health • Health data Analytics for Security and Privacy • E-health Software and Hardware Security • Embedded Security for e-health - Applications in P4 medicine
Author: Islem Rekik
Publisher:
ISBN: 9783030876036
Category :
Languages : en
Pages : 0
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Book Description
This book constitutes the proceedings of the 4th International Workshop on Predictive Intelligence in Medicine, PRIME 2021, held in conjunction with MICCAI 2021, in Strasbourg, France, in October 2021.* The 25 papers presented in this volume were carefully reviewed and selected for inclusion in this book. The contributions describe new cutting-edge predictive models and methods that solve challenging problems in the medical field for a high-precision predictive medicine. *The workshop was held virtually.
