Book Titled Clinical Intelligence Shows How to Reduce Medical Errors Using Big Data Analytics Techniques, Machine Leaning
Online PR News – 08-May-2016 – Washington, D.C. – Washington, D.C. (May 9, 2016) – Johns Hopkins University Medical School announced that medical errors are the 3rd cause of death in America. A book titled Clinical Intelligence: The Big Data Analytics Revolution in Healthcare reveals data-driven methods to predict and prevent medical errors. The book applies big data analytics methods such as machine learning to clinical data, in order to improve healthcare quality and reduce costs.
“Prediction is a powerful tool that allows practitioners apply preventive measures”, said the author, Peter Ghavami, Ph.D. He added “There is a clear under-investment in the industry to use information technology and in particular data analytics to eliminate medical errors. We can prevent escalating medical conditions, medication errors and procedure mistakes by predicting them before they occur, using big data analytics techniques with clinical data.”
Several universities have announced their intent to adopt Clinical Intelligence as standard text book for graduate courses in Public Health Management and Data Analytics.
The book includes 10 chapters that study the application of data analytics to medical, data mining, clinical and healthcare data. Each chapter covers a wide range of topics from data curation, data visualization, health quality metrics, financial coding optimization, medical prediction, population health management, clinical pathways, medical coding automation and fraud detection.
The Clinical Intelligence book is the result of more than 15 years of experience in clinical data analytics and informatics by Peter Ghavami, Ph.D., a leading international consultant and author of best-selling technology books (www.linkedin.com/in/PeterGhavami). According to Amazon’s sales records, Clinical Intelligence is a best-selling books in clinical data analytics category.
The book covers topics that are important to big data management and analysis in healthcare. “There are amazing insights and opportunities in clinical data mining”, said Peter Ghavami, Ph.D., “This book is fun and easy to read. It’s a must read for everyone who is interested in monetizing clinical data.”
“Clinical Intelligence is an important book because it packs more than 100 analytics methods and use-cases into one handbook”, remarked Peter Ghavami, Ph.D., “Data mining and machine learning are going to unlock the information in our clinical data in a big way. If we’re serious about improving healthcare and reducing the cost of care, we must apply big data analytics techniques described in this book”.
Hospitals, Pharmaceuticals, Insurance companies and healthcare application providers will benefit from this book as they launch their big data analytics initiatives. They can address their big data analytics needs with the contents of this book.
More information about the book can be found at: http://www.amazon.com/Clinical-Intelligence-Analytics-Revolution-Healthcare/dp/1500428590.
The book is written for IT leaders, hospital administrators, healthcare executive and practitioners, CIO, CTO, Chief Data Officers, IT professionals, data analysts and data scientists who want to learn modern analytics methods to analyze their big data assets, create data ingestion pipelines, and develop data analytics solutions with healthcare information.
About the Author: Peter Ghavami, Ph.D. is a world renowned consultant and best-selling author of several IT books. He has been consultant and advisor to many Fortune 500 companies in the world for IT strategy, big data analytics, innovation and new technology development. His book on Hadoop data governance titled “Big Data Governance” supplements his Clinical Intelligence book. His first book titled “Lean, Agile and Six Sigma IT Management” is still widely used by IT professionals around the world. His books have been selected as text books by several universities. Dr. Ghavami has over 25 years of experience in technology development, IT leadership, data analytics, supercomputing, software engineering and innovation. He can be reached at firstname.lastname@example.org.