Advanced Prognostic Predictive Modelling in Healthcare Data Analytics - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Advanced Prognostic Predictive Modelling in Healthcare Data Analytics write by Sudipta Roy. This book was released on 2021-04-22. Advanced Prognostic Predictive Modelling in Healthcare Data Analytics available in PDF, EPUB and Kindle. This book discusses major technical advancements and research findings in the field of prognostic modelling in healthcare image and data analysis. The use of prognostic modelling as predictive models to solve complex problems of data mining and analysis in health care is the feature of this book. The book examines the recent technologies and studies that reached the practical level and becoming available in preclinical and clinical practices in computational intelligence. The main areas of interest covered in this book are highest quality, original work that contributes to the basic science of processing, analysing and utilizing all aspects of advanced computational prognostic modelling in healthcare image and data analysis.
Prognostic Models in Healthcare: AI and Statistical Approaches
Prognostic Models in Healthcare: AI and Statistical Approaches - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Prognostic Models in Healthcare: AI and Statistical Approaches write by Tanzila Saba. This book was released on 2022-07-06. Prognostic Models in Healthcare: AI and Statistical Approaches available in PDF, EPUB and Kindle. This book focuses on contemporary technologies and research in computational intelligence that has reached the practical level and is now accessible in preclinical and clinical settings. This book's principal objective is to thoroughly understand significant technological breakthroughs and research results in predictive modeling in healthcare imaging and data analysis. Machine learning and deep learning could be used to fully automate the diagnosis and prognosis of patients in medical fields. The healthcare industry's emphasis has evolved from a clinical-centric to a patient-centric model. However, it is still facing several technical, computational, and ethical challenges. Big data analytics in health care is becoming a revolution in technical as well as societal well-being viewpoints. Moreover, in this age of big data, there is increased access to massive amounts of regularly gathered data from the healthcare industry that has necessitated the development of predictive models and automated solutions for the early identification of critical and chronic illnesses. The book contains high-quality, original work that will assist readers in realizing novel applications and contexts for deep learning architectures and algorithms, making it an indispensable reference guide for academic researchers, professionals, industrial software engineers, and innovative model developers in healthcare industry.
Predictive Modeling in Biomedical Data Mining and Analysis
Predictive Modeling in Biomedical Data Mining and Analysis - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Predictive Modeling in Biomedical Data Mining and Analysis write by Sudipta Roy. This book was released on 2022-08-28. Predictive Modeling in Biomedical Data Mining and Analysis available in PDF, EPUB and Kindle. Predictive Modeling in Biomedical Data Mining and Analysis presents major technical advancements and research findings in the field of machine learning in biomedical image and data analysis. The book examines recent technologies and studies in preclinical and clinical practice in computational intelligence. The authors present leading-edge research in the science of processing, analyzing and utilizing all aspects of advanced computational machine learning in biomedical image and data analysis. As the application of machine learning is spreading to a variety of biomedical problems, including automatic image segmentation, image classification, disease classification, fundamental biological processes, and treatments, this is an ideal reference. Machine Learning techniques are used as predictive models for many types of applications, including biomedical applications. These techniques have shown impressive results across a variety of domains in biomedical engineering research. Biology and medicine are data-rich disciplines, but the data are complex and often ill-understood, hence the need for new resources and information. Includes predictive modeling algorithms for both Supervised Learning and Unsupervised Learning for medical diagnosis, data summarization and pattern identification Offers complete coverage of predictive modeling in biomedical applications, including data visualization, information retrieval, data mining, image pre-processing and segmentation, mathematical models and deep neural networks Provides readers with leading-edge coverage of biomedical data processing, including high dimension data, data reduction, clinical decision-making, deep machine learning in large data sets, multimodal, multi-task, and transfer learning, as well as machine learning with Internet of Biomedical Things applications
Predictive Analytics of Psychological Disorders in Healthcare
Predictive Analytics of Psychological Disorders in Healthcare - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Predictive Analytics of Psychological Disorders in Healthcare write by Mamta Mittal. This book was released on 2022-05-20. Predictive Analytics of Psychological Disorders in Healthcare available in PDF, EPUB and Kindle. This book discusses an interdisciplinary field which combines two major domains: healthcare and data analytics. It presents research studies by experts helping to fight discontent, distress, anxiety and unrealized potential by using mathematical models, machine learning, artificial intelligence, etc. and take preventive measures beforehand. Psychological disorders and biological abnormalities are significantly related with the applications of cognitive illnesses which has increased significantly in contemporary years and needs rapid investigation. The research content of this book is helpful for psychological undergraduates, health workers and their trainees, therapists, medical psychologists, and nurses.
Clinical Prediction Models
Clinical Prediction Models - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Clinical Prediction Models write by Ewout Steyerberg. This book was released on 2010-10-21. Clinical Prediction Models available in PDF, EPUB and Kindle. Prediction models are important in various fields, including medicine, physics, meteorology, and finance. Prediction models will become more relevant in the medical field with the increase in knowledge on potential predictors of outcome, e.g. from genetics. Also, the number of applications will increase, e.g. with targeted early detection of disease, and individualized approaches to diagnostic testing and treatment. The current era of evidence-based medicine asks for an individualized approach to medical decision-making. Evidence-based medicine has a central place for meta-analysis to summarize results from randomized controlled trials; similarly prediction models may summarize the effects of predictors to provide individu- ized predictions of a diagnostic or prognostic outcome. Why Read This Book? My motivation for working on this book stems primarily from the fact that the development and applications of prediction models are often suboptimal in medical publications. With this book I hope to contribute to better understanding of relevant issues and give practical advice on better modelling strategies than are nowadays widely used. Issues include: (a) Better predictive modelling is sometimes easily possible; e.g. a large data set with high quality data is available, but all continuous predictors are dich- omized, which is known to have several disadvantages.
