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Book Handbook of Research on Disease Prediction Through Data Analytics and Machine Learning

Download or read book Handbook of Research on Disease Prediction Through Data Analytics and Machine Learning written by Rani, Geeta and published by IGI Global. This book was released on 2020-10-16 with total page 586 pages. Available in PDF, EPUB and Kindle. Book excerpt: By applying data analytics techniques and machine learning algorithms to predict disease, medical practitioners can more accurately diagnose and treat patients. However, researchers face problems in identifying suitable algorithms for pre-processing, transformations, and the integration of clinical data in a single module, as well as seeking different ways to build and evaluate models. The Handbook of Research on Disease Prediction Through Data Analytics and Machine Learning is a pivotal reference source that explores the application of algorithms to making disease predictions through the identification of symptoms and information retrieval from images such as MRIs, ECGs, EEGs, etc. Highlighting a wide range of topics including clinical decision support systems, biomedical image analysis, and prediction models, this book is ideally designed for clinicians, physicians, programmers, computer engineers, IT specialists, data analysts, hospital administrators, researchers, academicians, and graduate and post-graduate students.

Book Clinical Prediction Models

Download or read book Clinical Prediction Models written by Ewout W. Steyerberg and published by Springer. This book was released on 2019-07-22 with total page 574 pages. Available in PDF, EPUB and Kindle. Book excerpt: The second edition of this volume provides insight and practical illustrations on how modern statistical concepts and regression methods can be applied in medical prediction problems, including diagnostic and prognostic outcomes. Many advances have been made in statistical approaches towards outcome prediction, but a sensible strategy is needed for model development, validation, and updating, such that prediction models can better support medical practice. There is an increasing need for personalized evidence-based medicine that uses an individualized approach to medical decision-making. In this Big Data era, there is expanded access to large volumes of routinely collected data and an increased number of applications for prediction models, such as targeted early detection of disease and individualized approaches to diagnostic testing and treatment. Clinical Prediction Models presents a practical checklist that needs to be considered for development of a valid prediction model. Steps include preliminary considerations such as dealing with missing values; coding of predictors; selection of main effects and interactions for a multivariable model; estimation of model parameters with shrinkage methods and incorporation of external data; evaluation of performance and usefulness; internal validation; and presentation formatting. The text also addresses common issues that make prediction models suboptimal, such as small sample sizes, exaggerated claims, and poor generalizability. The text is primarily intended for clinical epidemiologists and biostatisticians. Including many case studies and publicly available R code and data sets, the book is also appropriate as a textbook for a graduate course on predictive modeling in diagnosis and prognosis. While practical in nature, the book also provides a philosophical perspective on data analysis in medicine that goes beyond predictive modeling. Updates to this new and expanded edition include: • A discussion of Big Data and its implications for the design of prediction models • Machine learning issues • More simulations with missing ‘y’ values • Extended discussion on between-cohort heterogeneity • Description of ShinyApp • Updated LASSO illustration • New case studies

Book Intelligent Fault Diagnosis and Remaining Useful Life Prediction of Rotating Machinery

Download or read book Intelligent Fault Diagnosis and Remaining Useful Life Prediction of Rotating Machinery written by Yaguo Lei and published by Butterworth-Heinemann. This book was released on 2016-11-02 with total page 378 pages. Available in PDF, EPUB and Kindle. Book excerpt: Intelligent Fault Diagnosis and Remaining Useful Life Prediction of Rotating Machinery provides a comprehensive introduction of intelligent fault diagnosis and RUL prediction based on the current achievements of the author's research group. The main contents include multi-domain signal processing and feature extraction, intelligent diagnosis models, clustering algorithms, hybrid intelligent diagnosis strategies, and RUL prediction approaches, etc. This book presents fundamental theories and advanced methods of identifying the occurrence, locations, and degrees of faults, and also includes information on how to predict the RUL of rotating machinery. Besides experimental demonstrations, many application cases are presented and illustrated to test the methods mentioned in the book. This valuable reference provides an essential guide on machinery fault diagnosis that helps readers understand basic concepts and fundamental theories. Academic researchers with mechanical engineering or computer science backgrounds, and engineers or practitioners who are in charge of machine safety, operation, and maintenance will find this book very useful. - Provides a detailed background and roadmap of intelligent diagnosis and RUL prediction of rotating machinery, involving fault mechanisms, vibration characteristics, health indicators, and diagnosis and prognostics - Presents basic theories, advanced methods, and the latest contributions in the field of intelligent fault diagnosis and RUL prediction - Includes numerous application cases, and the methods, algorithms, and models introduced in the book are demonstrated by industrial experiences

Book Diagnosis and Prediction

    Book Details:
  • Author : Seymour Geisser
  • Publisher : Springer Science & Business Media
  • Release : 2012-12-06
  • ISBN : 1461215404
  • Pages : 153 pages

Download or read book Diagnosis and Prediction written by Seymour Geisser and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 153 pages. Available in PDF, EPUB and Kindle. Book excerpt: A collection of refereed papers from a six-week workshop on statistics in the health sciences, that brought together theoretical and applied statisticians from universities, medical and public health schools, government and private research institutions, and pharmaceutical companies involved in prediction problems in the life and social sciences and in diagnostic and screening tests. A number of papers with applications were presented and particularly lively discussions ensued involving the critical issues and difficulties in using and interpreting diagnostic tests and implementing mass screening programs. The prediction or controlling future events, such as survival, comparative survival and survival post intervention for a disease or even for certain biological or natural events was also represented by participants who presented work that devised predictive methodology for a variety of problems mainly from a Bayesian perspective.

Book Reflections on 25 Years of Analysis  Diagnosis  and Prediction

Download or read book Reflections on 25 Years of Analysis Diagnosis and Prediction written by Climate Prediction Center (U.S.) and published by . This book was released on 2004 with total page 112 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Book Evidence Based Diagnosis

    Book Details:
  • Author : Mark H. Ebell
  • Publisher : Springer Science & Business Media
  • Release : 2013-03-09
  • ISBN : 1475735146
  • Pages : 402 pages

Download or read book Evidence Based Diagnosis written by Mark H. Ebell and published by Springer Science & Business Media. This book was released on 2013-03-09 with total page 402 pages. Available in PDF, EPUB and Kindle. Book excerpt: Covering a full range of topics from cardiovascular and pulmonary disease to ophthalmology, hematology and pediatrics, this is the only single volume, quick reference designed for use in daily practice. The 150+ clinical prediction rules as well as the background information necessary to determine its validity and relevance are essential for every physician in a time of limited health care resources. Designed as an aid in diagnosis and treatment, these rules allow more accurate diagnosis and treatment decisions while eliminating superfluous testing.

Book The Statistical Evaluation of Medical Tests for Classification and Prediction

Download or read book The Statistical Evaluation of Medical Tests for Classification and Prediction written by Margaret Sullivan Pepe and published by OUP Oxford. This book was released on 2003-03-13 with total page 319 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book describes statistical techniques for the design and evaluation of research studies on medical diagnostic tests, screening tests, biomarkers and new technologies for classification and prediction in medicine.

Book Intelligent Modelling  Prediction  and Diagnosis from Epidemiological Data

Download or read book Intelligent Modelling Prediction and Diagnosis from Epidemiological Data written by Siddhartha Bhattacharyya and published by . This book was released on 2021 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: "Intelligent Modelling, Prediction, and Diagnosis from Epidemiological Data COVID-19 and Beyond is a handy treatise to elicit and elaborate possible intelligent mechanisms for modeling, prediction, diagnosis and early detection of diseases arising out of outbreaks of different epidemics with special reference to COVID-19. Starting with a formal introduction of the human immune systems, this book focuses on the epidemiological aspects with due cognizance to modeling, prevention and diagnosis of epidemics. In addition, it also deals with evolving decisions on post-pandemic economic-social structure. The book offers comprehensive coverage of the most essential topics, including: A general overview of pandemics and their outbreak behavior. A detailed overview of CI techniques. Intelligent modeling, prediction and diagnostic measures for pandemics. Prognostic models. Post-pandemic socio-economic structure. The accompanying case studies are based on real-world data sets available till date. While other books may deal with this Covid-19 pandemic, none features the human immune systems as well as influences on the environmental disorder due to the ongoing pandemic. The book is primarily intended to come to the benefit of medical professionals and healthcare workers along with the virologists who are essentially the frontline fighters of Covid-19 pandemic. In addition, it would also serve as an essential resource for relevant researchers in this interdisciplinary field apart from tutors, post-graduate and under-graduate students of information sciences"--

Book Oxford Handbook of Clinical Diagnosis

Download or read book Oxford Handbook of Clinical Diagnosis written by Huw Llewelyn and published by Oxford University Press, USA. This book was released on 2014 with total page 683 pages. Available in PDF, EPUB and Kindle. Book excerpt: This handbook describes the diagnostic process clearly and logically, aiding medical students and others who wish to improve their diagnostic performance and to learn more about the diagnostic process.

Book Machine Learning Models and Algorithms for Big Data Classification

Download or read book Machine Learning Models and Algorithms for Big Data Classification written by Shan Suthaharan and published by Springer. This book was released on 2015-10-20 with total page 364 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents machine learning models and algorithms to address big data classification problems. Existing machine learning techniques like the decision tree (a hierarchical approach), random forest (an ensemble hierarchical approach), and deep learning (a layered approach) are highly suitable for the system that can handle such problems. This book helps readers, especially students and newcomers to the field of big data and machine learning, to gain a quick understanding of the techniques and technologies; therefore, the theory, examples, and programs (Matlab and R) presented in this book have been simplified, hardcoded, repeated, or spaced for improvements. They provide vehicles to test and understand the complicated concepts of various topics in the field. It is expected that the readers adopt these programs to experiment with the examples, and then modify or write their own programs toward advancing their knowledge for solving more complex and challenging problems. The presentation format of this book focuses on simplicity, readability, and dependability so that both undergraduate and graduate students as well as new researchers, developers, and practitioners in this field can easily trust and grasp the concepts, and learn them effectively. It has been written to reduce the mathematical complexity and help the vast majority of readers to understand the topics and get interested in the field. This book consists of four parts, with the total of 14 chapters. The first part mainly focuses on the topics that are needed to help analyze and understand data and big data. The second part covers the topics that can explain the systems required for processing big data. The third part presents the topics required to understand and select machine learning techniques to classify big data. Finally, the fourth part concentrates on the topics that explain the scaling-up machine learning, an important solution for modern big data problems.

Book Analytical Methods for Diagnosis and Prediction of Health Conditions

Download or read book Analytical Methods for Diagnosis and Prediction of Health Conditions written by Tyler Austin Davis and published by . This book was released on 2023 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Recent years have seen a tremendous amount of growth in the performance and adoption of artificial intelligence (AI) and machine learning (ML) systems. These systems now permeate our lives, underpinning everything from web search to credit card fraud detection and photography. In principle, these advancements could also be applied to the domain of healthcare, where they could improve patient outcomes.However, despite the almost fifty years that have elapsed since the first National Institutes of Health AI in Medicine (AIM) workshop in 1973 and the ubiquity of AI systems in our daily lives, AIM has not yet lived up to its lofty promises. AIM systems have seen limited deployment due to challenges including data missingness, data heterogeneity, explainability, and generalizability across variances in patient populations. The recent increase in the availability of electronic health record information, the variety and cost-effectiveness of mobile sensors, and the capabilities of machine learning algorithms promise to help improve healthcare delivery if challenges can be overcome. Through techniques such as interpretable analysis of heterogeneous information networks and missingness-aware modeling, we demonstrate that the challenges of AI in Medicine can be overcome in order to improve healthcare access, aid physicians, and generate new insights into disease.

Book Assessment of Diagnostic Technology in Health Care

Download or read book Assessment of Diagnostic Technology in Health Care written by Institute of Medicine and published by National Academies Press. This book was released on 1989-02-01 with total page 152 pages. Available in PDF, EPUB and Kindle. Book excerpt: Technology assessment can lead to the rapid application of essential diagnostic technologies and prevent the wide diffusion of marginally useful methods. In both of these ways, it can increase quality of care and decrease the cost of health care. This comprehensive monograph carefully explores methods of and barriers to diagnostic technology assessment and describes both the rationale and the guidelines for meaningful evaluation. While proposing a multi-institutional approach, it emphasizes some of the problems involved and defines a mechanism for improving the evaluation and use of medical technology and essential resources needed to enhance patient care.

Book Artificial Intelligence in Medicine

Download or read book Artificial Intelligence in Medicine written by Martin Michalowski and published by Springer Nature. This book was released on 2020-09-25 with total page 505 pages. Available in PDF, EPUB and Kindle. Book excerpt: The LNAI 12299 constitutes the papers of the 18th International Conference on Artificial Intelligence in Medicine, AIME 2020, which will be held online in August 2020. The 42 full papers presented together with 1short papers in this volume were carefully reviewed and selected from a total of 103 submissions. The AIME 2020 goals were to present and consolidate the international state of the art of AI in biomedical research from the perspectives of theory, methodology, systems, and applications.

Book Improving Diagnosis in Health Care

    Book Details:
  • Author : National Academies of Sciences, Engineering, and Medicine
  • Publisher : National Academies Press
  • Release : 2015-12-29
  • ISBN : 0309377722
  • Pages : 473 pages

Download or read book Improving Diagnosis in Health Care written by National Academies of Sciences, Engineering, and Medicine and published by National Academies Press. This book was released on 2015-12-29 with total page 473 pages. Available in PDF, EPUB and Kindle. Book excerpt: Getting the right diagnosis is a key aspect of health care - it provides an explanation of a patient's health problem and informs subsequent health care decisions. The diagnostic process is a complex, collaborative activity that involves clinical reasoning and information gathering to determine a patient's health problem. According to Improving Diagnosis in Health Care, diagnostic errors-inaccurate or delayed diagnoses-persist throughout all settings of care and continue to harm an unacceptable number of patients. It is likely that most people will experience at least one diagnostic error in their lifetime, sometimes with devastating consequences. Diagnostic errors may cause harm to patients by preventing or delaying appropriate treatment, providing unnecessary or harmful treatment, or resulting in psychological or financial repercussions. The committee concluded that improving the diagnostic process is not only possible, but also represents a moral, professional, and public health imperative. Improving Diagnosis in Health Care, a continuation of the landmark Institute of Medicine reports To Err Is Human (2000) and Crossing the Quality Chasm (2001), finds that diagnosis-and, in particular, the occurrence of diagnostic errorsâ€"has been largely unappreciated in efforts to improve the quality and safety of health care. Without a dedicated focus on improving diagnosis, diagnostic errors will likely worsen as the delivery of health care and the diagnostic process continue to increase in complexity. Just as the diagnostic process is a collaborative activity, improving diagnosis will require collaboration and a widespread commitment to change among health care professionals, health care organizations, patients and their families, researchers, and policy makers. The recommendations of Improving Diagnosis in Health Care contribute to the growing momentum for change in this crucial area of health care quality and safety.

Book Clinical Prediction Rules for Assisting Diagnosis

Download or read book Clinical Prediction Rules for Assisting Diagnosis written by Sharon Lea Sanders and published by . This book was released on 2015 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Book Decision Making in Health and Medicine

Download or read book Decision Making in Health and Medicine written by M. G. Myriam Hunink and published by Cambridge University Press. This book was released on 2014-10-16 with total page 447 pages. Available in PDF, EPUB and Kindle. Book excerpt: A guide for everyone involved in medical decision making to plot a clear course through complex and conflicting benefits and risks.

Book Smart Medical Data Sensing and IoT Systems Design in Healthcare

Download or read book Smart Medical Data Sensing and IoT Systems Design in Healthcare written by Chakraborty, Chinmay and published by IGI Global. This book was released on 2019-09-20 with total page 288 pages. Available in PDF, EPUB and Kindle. Book excerpt: Smart healthcare technology improves the diagnosis and treatment of patients, provides easy access to medical facilities and emergency care services, and minimizes the gaps between patients and healthcare providers. While clinical data protection remains a major challenge, innovations such as the internet of medical things and smart healthcare systems increase the efficiency and quality of patient care. Healthcare technology can only become faster, more profitable, and more flexible as additional research on its advancements is conducted and collected. Smart Medical Data Sensing and IoT Systems Design in Healthcare is an essential reference source that focuses on robust and easy solutions for the delivery of medical information from patients to doctors and explores low-cost, high-performance, highly efficient, deployable IoT system options in healthcare systems. Featuring research on topics such as hospital management systems, electronic health records, and bio-signals, this book is ideally designed for technologists, engineers, scientists, clinicians, biomedical engineers, hospital directors, doctors, nurses, healthcare practitioners, telemedical agents, students, and academicians seeking coverage on the latest technological developments in medical data analysis and connectivity.