Data Mining Healthcare And Clinical Databases
Download Data Mining Healthcare And Clinical Databases full books in PDF, epub, and Kindle. Read online free Data Mining Healthcare And Clinical Databases ebook anywhere anytime directly on your device. Fast Download speed and no annoying ads. We cannot guarantee that every ebooks is available!
Author | : Patricia Cerrito |
Publisher | : Lulu.com |
Total Pages | : 483 |
Release | : 2010-07-18 |
Genre | : Science |
ISBN | : 0557565766 |
This text will demonstrate the different data mining techniques and how they can be used to investigate patient records and public health records with the dual objective of decreasing costs while improving the quality of care. In this chapter, we give a basic introduction to the data mining process (section 3). We also give basic information concerning the datasets that we will be using to demonstrate the techniques (section 2). In subsequent chapters, we will examine specific questions to demonstrate how the various data mining techniques can be used to investigate the electronic medical record, billing data, and other healthcare databases to satisfy our objectives.
Author | : Cerrito, Patricia |
Publisher | : IGI Global |
Total Pages | : 370 |
Release | : 2010-06-30 |
Genre | : Computers |
ISBN | : 1615209069 |
"This book shows how the investigation of healthcare databases can be used to examine physician decisions to develop evidence-based treatment guidelines that optimize patient outcomes"--Provided by publisher.
Author | : Cerrito, Patricia |
Publisher | : IGI Global |
Total Pages | : 464 |
Release | : 2010-02-28 |
Genre | : Computers |
ISBN | : 1615207244 |
"Because so much data is now becoming readily available to investigate health outcomes, it is important to examine just how statistical models are used to do this. This book studies health outcomes research using data mining techniques"--Provided by publisher.
Author | : Berka, Petr |
Publisher | : IGI Global |
Total Pages | : 464 |
Release | : 2009-02-28 |
Genre | : Computers |
ISBN | : 1605662194 |
The healthcare industry produces a constant flow of data, creating a need for deep analysis of databases through data mining tools and techniques resulting in expanded medical research, diagnosis, and treatment. Data Mining and Medical Knowledge Management: Cases and Applications presents case studies on applications of various modern data mining methods in several important areas of medicine, covering classical data mining methods, elaborated approaches related to mining in electroencephalogram and electrocardiogram data, and methods related to mining in genetic data. A premier resource for those involved in data mining and medical knowledge management, this book tackles ethical issues related to cost-sensitive learning in medicine and produces theoretical contributions concerning general problems of data, information, knowledge, and ontologies.
Author | : Chandan K. Reddy |
Publisher | : CRC Press |
Total Pages | : 756 |
Release | : 2015-06-23 |
Genre | : Business & Economics |
ISBN | : 148223212X |
At the intersection of computer science and healthcare, data analytics has emerged as a promising tool for solving problems across many healthcare-related disciplines. Supplying a comprehensive overview of recent healthcare analytics research, Healthcare Data Analytics provides a clear understanding of the analytical techniques currently available
Author | : Krzysztof J. Cios |
Publisher | : Physica |
Total Pages | : 528 |
Release | : 2001-01-12 |
Genre | : Computers |
ISBN | : |
Modern medicine generates, almost daily, huge amounts of heterogeneous data. For example, medical data may contain SPECT images, signals like ECG, clinical information like temperature, cholesterol levels, etc., as well as the physician's interpretation. Those who deal with such data understand that there is a widening gap between data collection and data comprehension. Computerized techniques are needed to help humans address this problem. This volume is devoted to the relatively young and growing field of medical data mining and knowledge discovery. As more and more medical procedures employ imaging as a preferred diagnostic tool, there is a need to develop methods for efficient mining in databases of images. Other significant features are security and confidentiality concerns. Moreover, the physician's interpretation of images, signals, or other technical data, is written in unstructured English which is very difficult to mine. This book addresses all these specific features.
Author | : Carlos Fernández Llatas |
Publisher | : Humana Press |
Total Pages | : 0 |
Release | : 2014-11-24 |
Genre | : Science |
ISBN | : 9781493919840 |
This volume complies a set of Data Mining techniques and new applications in real biomedical scenarios. Chapters focus on innovative data mining techniques, biomedical datasets and streams analysis, and real applications. Written in the highly successful Methods in Molecular Biology series format, chapters are thought to show to Medical Doctors and Engineers the new trends and techniques that are being applied to Clinical Medicine with the arrival of new Information and Communication technologies Authoritative and practical, Data Mining in Clinical Medicine seeks to aid scientists with new approaches and trends in the field.
Author | : Nilanjan Dey |
Publisher | : Academic Press |
Total Pages | : 342 |
Release | : 2018-11-15 |
Genre | : Science |
ISBN | : 0128156368 |
Healthcare Data Analytics and Management help readers disseminate cutting-edge research that delivers insights into the analytic tools, opportunities, novel strategies, techniques and challenges for handling big data, data analytics and management in healthcare. As the rapidly expanding and heterogeneous nature of healthcare data poses challenges for big data analytics, this book targets researchers and bioengineers from areas of machine learning, data mining, data management, and healthcare providers, along with clinical researchers and physicians who are interested in the management and analysis of healthcare data. Covers data analysis, management and security concepts and tools in the healthcare domain Highlights electronic medical health records and patient information records Discusses the different techniques to integrate Big data and Internet-of-Things in healthcare, including machine learning and data mining Includes multidisciplinary contributions in relation to healthcare applications and challenges
Author | : Cerrito, Patricia |
Publisher | : IGI Global |
Total Pages | : 410 |
Release | : 2009-08-31 |
Genre | : Computers |
ISBN | : 1605667536 |
The quest for quality in healthcare has led to attempts to develop models to determine which providers have the highest quality in healthcare, with the best outcomes for patients. Text Mining Techniques for Healthcare Provider Quality Determination: Methods for Rank Comparisons discusses the general practice of defining a patient severity index in order to make risk adjustments to compare patient outcomes across multiple providers with the intent of ranking the providers in terms of quality. This innovative reference source, valuable to medical practitioners, researchers, and academicians, brings together research from across the globe focusing on how severity indices are generally defined when determining the best outcome for patient
Author | : MIT Critical Data |
Publisher | : Springer |
Total Pages | : 435 |
Release | : 2016-09-09 |
Genre | : Medical |
ISBN | : 3319437429 |
This book trains the next generation of scientists representing different disciplines to leverage the data generated during routine patient care. It formulates a more complete lexicon of evidence-based recommendations and support shared, ethical decision making by doctors with their patients. Diagnostic and therapeutic technologies continue to evolve rapidly, and both individual practitioners and clinical teams face increasingly complex ethical decisions. Unfortunately, the current state of medical knowledge does not provide the guidance to make the majority of clinical decisions on the basis of evidence. The present research infrastructure is inefficient and frequently produces unreliable results that cannot be replicated. Even randomized controlled trials (RCTs), the traditional gold standards of the research reliability hierarchy, are not without limitations. They can be costly, labor intensive, and slow, and can return results that are seldom generalizable to every patient population. Furthermore, many pertinent but unresolved clinical and medical systems issues do not seem to have attracted the interest of the research enterprise, which has come to focus instead on cellular and molecular investigations and single-agent (e.g., a drug or device) effects. For clinicians, the end result is a bit of a “data desert” when it comes to making decisions. The new research infrastructure proposed in this book will help the medical profession to make ethically sound and well informed decisions for their patients.