Download or read book Practical Predictive Analytics and Decisioning Systems for Medicine written by Gary D. Miner and published by Academic Press. This book was released on 2014-09-27 with total page 1111 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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

Download or read book Preventive and Predictive Genetics Towards Personalised Medicine written by Godfrey Grech and published by Springer. This book was released on 2015-06-24 with total page 388 pages. Available in PDF, EPUB and Kindle. Book excerpt: Pharmacogenomics supports personalized medicine by translating genome-based knowledge into clinical practice, offering enhanced benefit for patients and health-care systems at large. Current routine practice for diagnosing and treating patients is conducted by correlating parameters such as age, gender and weight with risks and expected treatment outcomes. In the new era of personalized medicine the healthcare provider is equipped with improved ability to prevent, diagnose, treat and predict outcomes on the basis of complex information sources, including genetic and genomic data. Targeted therapy and reliable prediction of expected outcomes offer patients access to better healthcare management, by way of identifying the therapies effective for the relevant patient group, avoiding prescription of unnecessary treatment and reducing the likelihood of developing adverse drug reactions.

Download or read book Applied Predictive Modeling written by Max Kuhn and published by Springer Science & Business Media. This book was released on 2013-05-17 with total page 595 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Predictive Medicine written by Emmanuel Fombu and published by Business Expert Press. This book was released on 2020-01-10 with total page 237 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Predictive Intelligence in Medicine written by Islem Rekik and published by Springer. This book was released on 2019-10-11 with total page 178 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Design and Analysis of Clinical Trials for Predictive Medicine written by Shigeyuki Matsui and published by CRC Press. This book was released on 2015-03-19 with total page 394 pages. Available in PDF, EPUB and Kindle. Book excerpt: Design and Analysis of Clinical Trials for Predictive Medicine provides statistical guidance on conducting clinical trials for predictive medicine. It covers statistical topics relevant to the main clinical research phases for developing molecular diagnostics and therapeutics-from identifying molecular biomarkers using DNA microarrays to confirming

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 558 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

Download or read book Predictive Health written by Kenneth L. Brigham and published by . This book was released on 2012-10-02 with total page 258 pages. Available in PDF, EPUB and Kindle. Book excerpt: Our health care system is crippled by desperate efforts to prevent the inevitable. A third of the national Medicare budget—nearly 175 billion—is spent on the final year of life, and a third of that amount on the final month, often on expensive (and futile) treatments. Such efforts betray a fundamental flaw in how we think about healthcare: we squander resources on hopeless situations, instead of using them to actually improve health. In Predictive Health, distinguished doctors Kenneth Brigham and Michael M.E. Johns propose a solution: invest earlier—and use science and technology to make healthcare more available and affordable. Every child would begin life with a post-natal genetic screen, when potential risk—say for type II diabetes or heart disease—would be found. More data on biology, behavior, and environment would be captured throughout her life. Using this information, health-care workers and the people they care for could forge personal strategies for healthier living long before a small glitch blows up into major disease. This real health care wouldn’t just replace much of modern disease care—it would make it obsolete. The result, according to Brigham and Johns, will be a life defined by a long stay at top physical and mental form, rather than an early peak and long decline. Accomplishing this goal will require new tools, new clinics, fewer doctors and more mentors, smarter companies, and engaged patients. In short, it will require a revolution. Thanks to a decade-long collaboration between Brigham, Johns and others, it is already underway. An optimistic plan for reducing or eliminating many chronic diseases as well as reforming our faltering medical system, Predictive Health is a deeply knowledgeable, deeply humane proposal for how we can reallocate expenses and resources to prolong the best years of life, rather than extending the worst.

Download or read book Personalized Predictive Modeling in Type 1 Diabetes written by Eleni I. Georga and published by Academic Press. This book was released on 2017-12-11 with total page 253 pages. Available in PDF, EPUB and Kindle. Book excerpt: Personalized Predictive Modeling in Diabetes features state-of-the-art methodologies and algorithmic approaches which have been applied to predictive modeling of glucose concentration, ranging from simple autoregressive models of the CGM time series to multivariate nonlinear regression techniques of machine learning. Developments in the field have been analyzed with respect to: (i) feature set (univariate or multivariate), (ii) regression technique (linear or non-linear), (iii) learning mechanism (batch or sequential), (iv) development and testing procedure and (v) scaling properties. In addition, simulation models of meal-derived glucose absorption and insulin dynamics and kinetics are covered, as an integral part of glucose predictive models. This book will help engineers and clinicians to: select a regression technique which can capture both linear and non-linear dynamics in glucose metabolism in diabetes, and which exhibits good generalization performance under stationary and non-stationary conditions; ensure the scalability of the optimization algorithm (learning mechanism) with respect to the size of the dataset, provided that multiple days of patient monitoring are needed to obtain a reliable predictive model; select a features set which efficiently represents both spatial and temporal dependencies between the input variables and the glucose concentration; select simulation models of subcutaneous insulin absorption and meal absorption; identify an appropriate validation procedure, and identify realistic performance measures. Describes fundamentals of modeling techniques as applied to glucose control Covers model selection process and model validation Offers computer code on a companion website to show implementation of models and algorithms Features the latest developments in the field of diabetes predictive modeling

Download or read book Predictive Medicine written by Emanuel Cheraskin and published by Keats Publishing. This book was released on 1977 with total page 196 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Predictive Modeling of Drug Sensitivity written by Ranadip Pal and published by Academic Press. This book was released on 2016-11-15 with total page 356 pages. Available in PDF, EPUB and Kindle. Book excerpt: Predictive Modeling of Drug Sensitivity gives an overview of drug sensitivity modeling for personalized medicine that includes data characterizations, modeling techniques, applications, and research challenges. It covers the major mathematical techniques used for modeling drug sensitivity, and includes the requisite biological knowledge to guide a user to apply the mathematical tools in different biological scenarios. This book is an ideal reference for computer scientists, engineers, computational biologists, and mathematicians who want to understand and apply multiple approaches and methods to drug sensitivity modeling. The reader will learn a broad range of mathematical and computational techniques applied to the modeling of drug sensitivity, biological concepts, and measurement techniques crucial to drug sensitivity modeling, how to design a combination of drugs under different constraints, and the applications of drug sensitivity prediction methodologies. Applies mathematical and computational approaches to biological problems Covers all aspects of drug sensitivity modeling, starting from initial data generation to final experimental validation Includes the latest results on drug sensitivity modeling that is based on updated research findings Provides information on existing data and software resources for applying the mathematical and computational tools available

Download or read book Digital Health Approach for Predictive Preventive Personalised and Participatory Medicine written by Lotfi Chaari and published by Springer. This book was released on 2019-07-10 with total page 88 pages. Available in PDF, EPUB and Kindle. Book excerpt: This collection, entitled Digital Health for Predictive, Preventive, Personalized and Participatory Medicine contains the proceedings of the first International conference on digital healthtechnologies (ICDHT 2018). Ten recent contributions in the fields of Artificial Intelligence (AI) and machine learning, Internet of Things (IoT) and data analysis, all applied to digital health. This collection enables researchers to learn about recent advances in the above mentioned fields. It brings a technological viewpoint of P4 medicine. Readers will discover how advanced Information Technology (IT) tools can be used for healthcare. For instance, the use of connected objects to monitor physiological parameters is discussed. Moreover, even if compressed sensing is nowadays a common acquisition technique, its use for IoT is presented in this collection through one of the pioneer works in the field. In addition, the use of AI for epileptic seizure detection is also discussed as being one of the major concerns of predictive medicine both in industrialized and low-income countries. This work is edited by Prof. Lotfi Chaari, professor at the University of Sfax, and previously at the University of Toulouse. This work comes after more than ten years of expertise in the biomedical signal and image processing field.

Download or read book Human Motion Simulation written by Karim Abdel-Malek and published by Academic Press. This book was released on 2013-05-30 with total page 296 pages. Available in PDF, EPUB and Kindle. Book excerpt: Simulate realistic human motion in a virtual world with an optimization-based approach to motion prediction. With this approach, motion is governed by human performance measures, such as speed and energy, which act as objective functions to be optimized. Constraints on joint torques and angles are imposed quite easily. Predicting motion in this way allows one to use avatars to study how and why humans move the way they do, given specific scenarios. It also enables avatars to react to infinitely many scenarios with substantial autonomy. With this approach it is possible to predict dynamic motion without having to integrate equations of motion -- rather than solving equations of motion, this approach solves for a continuous time-dependent curve characterizing joint variables (also called joint profiles) for every degree of freedom. Introduces rigorous mathematical methods for digital human modelling and simulation Focuses on understanding and representing spatial relationships (3D) of biomechanics Develops an innovative optimization-based approach to predicting human movement Extensively illustrated with 3D images of simulated human motion (full color in the ebook version)

Download or read book Predictive Preventive and Personalised Medicine From Bench to Bedside written by Halina Podbielska and published by Springer Nature. This book was released on 2023-12-01 with total page 352 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume presents advanced bio/medical sciences with a particular value for translating research achievements into daily medical practice in the framework of Predictive, Preventive and Personalised Medicine (3PM/PPPM). First two decades of the 21st century are characterised by epidemics of non-communicable diseases such as many hundreds of millions of patients diagnosed with cardiovascular diseases and the type 2 diabetes mellitus, breast, lung, liver and prostate malignancies, neurological, sleep, mood and eye disorders, amongst others. Consequent socio-economic burden is tremendous. Unprecedented decrease in age of maladaptive individuals has been reported. The absolute majority of expanding non-communicable disorders carry a chronic character, over a couple of years progressing from reversible suboptimal health conditions to irreversible severe pathologies and cascading collateral complications. The paradigm change from reactive to predictive preventive and personalised medicine is essential to promote population health by application of individualised patient profiling, multi-parametric analysis leading to cost-effective targeted prevention. To this end, inadequate data for risk assessment on speed and urgency of COVID-19, combined with increased globalization of human society, led to the rapid spread of COVID-19. Despite an abundance of digital methods that could be used in slowing or stopping this virus and future pandemics, the world remains unprepared, and lessons have not been learned from previous cases of pandemics. The book presents PPPM strategies which might be of great clinical utility for future pandemics. In a long-term way, a significantly improved healthcare economy is one of the clear benefits of the proposed paradigm shift; a tight collaboration between all stakeholders including scientific community, healthcare providers, patient organisations, policy-makers and educators is analysed for the smooth implementation of the 3PM concepts. Further issues linked to big data management and medical ethics have to be carefully treated in the context of application of artificial intelligence in medicine.

Download or read book Digital Health in Focus of Predictive Preventive and Personalised Medicine written by Lotfi Chaari and published by Springer Nature. This book was released on 2020-09-30 with total page 164 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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

Download or read book Predictive Intelligence in Medicine written by Islem Rekik and published by Springer Nature. This book was released on 2023-10-07 with total page 306 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume LNCS 14277 constitutes the refereed proceedings of the 6th International Workshop, PRIME 2023, Held in Conjunction with MICCAI 2023, in October 2023, held in Vancouver, BC, Canada. The 24 full papers presented were carefully reviewed and selected from 27 submissions. This workshop intersects ideas from both machine learning and mathematical/statistical/physical modeling research directions in the hope to provide a deeper understanding of the foundations of predictive intelligence developed for medicine, as well as to where we currently stand and what we aspire to achieve through this field.

Download or read book Predictive Intelligence in Medicine written by Islem Rekik and published by Springer Nature. This book was released on 2020-10-01 with total page 212 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the proceedings of the Third International Workshop on Predictive Intelligence in Medicine, PRIME 2020, held in conjunction with MICCAI 2020, in Lima, Peru, in October 2020. The workshop was held virtually due to the COVID-19 pandemic. The 17 full and 2 short 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.