Practical Predictive Analytics and Decisioning Systems for Medicine: Informatics Accuracy and Cost-Effectiveness for Healthcare Administration and Delivery Including Medical Research
Gary D. Miner (Retired, currently Board Member for and teaching with the University of California, Irvine Predictive Analytics Certificate Program, USA),Linda A. Miner (Lecturer, Southern Nazarene University (SNU) and IHI Family Practice Medical Residency, Tulsa, OK, USA),Mitchell Goldstein (Associate Professor, Loma Linda Medical School, Loma Linda Medical Center, Los Angeles, CA, USA),Robert Nisbet (Researcher, University of California, Irvine Predictive Analytics Certification Program, University of California, Santa Barbara, USA),Nephi Walton (Pediatrics/Genetics fellow, Washington University, USA)
Practical Predictive Analytics and Decisioning Systems for Medicine: Informatics Accuracy and Cost-Effectiveness for Healthcare Administration and Delivery Including Medical Research
Gary D. Miner (Retired, currently Board Member for and teaching with the University of California, Irvine Predictive Analytics Certificate Program, USA),Linda A. Miner (Lecturer, Southern Nazarene University (SNU) and IHI Family Practice Medical Residency, Tulsa, OK, USA),Mitchell Goldstein (Associate Professor, Loma Linda Medical School, Loma Linda Medical Center, Los Angeles, CA, USA),Robert Nisbet (Researcher, University of California, Irvine Predictive Analytics Certification Program, University of California, Santa Barbara, USA),Nephi Walton (Pediatrics/Genetics fellow, Washington University, USA)
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.
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