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[ subject:"Data Mining." ]
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Clinical data mining for physician d...
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Cerrito, John, (1954-)
Clinical data mining for physician decision making and investigating health outcomesmethods for prediction and analysis /
紀錄類型:
書目-電子資源 : Monograph/item
正題名/作者:
Clinical data mining for physician decision making and investigating health outcomesPatricia Cerrito, John Cerrito.
其他題名:
methods for prediction and analysis /
其他作者:
Cerrito, John,
出版者:
Hershey, Pa. :IGI Global (701 E. Chocolate Avenue, Hershey, Pennsylvania, 17033, USA),c2010.
面頁冊數:
1 online resource (351 p.) :ill.
標題:
Medical informatics.
電子資源:
http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/978-1-61520-905-7
ISBN:
9781615209064 (ebook)
Clinical data mining for physician decision making and investigating health outcomesmethods for prediction and analysis /
Clinical data mining for physician decision making and investigating health outcomes
methods for prediction and analysis /[electronic resource] :Patricia Cerrito, John Cerrito. - Hershey, Pa. :IGI Global (701 E. Chocolate Avenue, Hershey, Pennsylvania, 17033, USA),c2010. - 1 online resource (351 p.) :ill.
Includes bibliographical references.
Preprocessing the data -- Errors and missing values in the dataset -- Introduction to the use of MEPS (medical expenditure panel survey) -- Preprocessing Medpar data -- Extracting data from the national inpatient sample -- Creating a one-to-one relationship in the data from a many-to-many -- Merging different datasets to allow for a complete analysis (inpatient, outpatient, physician visits, medications) -- Introduction to analysis using time components -- More survival data mining-multiple time of endpoints -- Using the data to define patient compliance -- Compression of diagnosis and procedure codes -- Comparisons of patient severity indices -- Decision trees and their development -- Example of diabetes using CMS data -- Example of breathing illnesses, asthma and COPD using MEPS data -- Example of wound care using Medpar data -- Discussion.
Restricted to subscribers or individual electronic text purchasers.
The investigation of healthcare databases can be used to examine physician decisions and develop evidence-based treatment guidelines that optimize patient outcomes. This book demonstrates how concern for detail in datasets and the use of data mining techniques can extract important and meaningful knowledge from healthcare databases. Basic information on processing data with step-by-step instructions is provided, allowing readers to use their own data and follow the instructions to find meaningful results.
Mode of access: World Wide Web.
ISBN: 9781615209064 (ebook)
LCCN: 2010006306Subjects--Topical Terms:
196487
Medical informatics.
LC Class. No.: R859.7.D36 / C55 2010e
Dewey Class. No.: 610.285
National Library of Medicine Call No.: W 26.55.I4 / C6415 2010e
Clinical data mining for physician decision making and investigating health outcomesmethods for prediction and analysis /
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Patricia Cerrito, John Cerrito.
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Includes bibliographical references.
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Preprocessing the data -- Errors and missing values in the dataset -- Introduction to the use of MEPS (medical expenditure panel survey) -- Preprocessing Medpar data -- Extracting data from the national inpatient sample -- Creating a one-to-one relationship in the data from a many-to-many -- Merging different datasets to allow for a complete analysis (inpatient, outpatient, physician visits, medications) -- Introduction to analysis using time components -- More survival data mining-multiple time of endpoints -- Using the data to define patient compliance -- Compression of diagnosis and procedure codes -- Comparisons of patient severity indices -- Decision trees and their development -- Example of diabetes using CMS data -- Example of breathing illnesses, asthma and COPD using MEPS data -- Example of wound care using Medpar data -- Discussion.
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The investigation of healthcare databases can be used to examine physician decisions and develop evidence-based treatment guidelines that optimize patient outcomes. This book demonstrates how concern for detail in datasets and the use of data mining techniques can extract important and meaningful knowledge from healthcare databases. Basic information on processing data with step-by-step instructions is provided, allowing readers to use their own data and follow the instructions to find meaningful results.
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http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/978-1-61520-905-7
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