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Statistics and Machine Learning Methods for EHR Data - From Data Extraction to Data Analytics (Paperback)
Loot Price: R1,456
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Statistics and Machine Learning Methods for EHR Data - From Data Extraction to Data Analytics (Paperback)
Series: Chapman & Hall/CRC Healthcare Informatics Series
Expected to ship within 12 - 17 working days
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The use of Electronic Health Records (EHR)/Electronic Medical
Records (EMR) data is becoming more prevalent for research.
However, analysis of this type of data has many unique
complications due to how they are collected, processed and types of
questions that can be answered. This book covers many important
topics related to using EHR/EMR data for research including data
extraction, cleaning, processing, analysis, inference, and
predictions based on many years of practical experience of the
authors. The book carefully evaluates and compares the standard
statistical models and approaches with those of machine learning
and deep learning methods and reports the unbiased comparison
results for these methods in predicting clinical outcomes based on
the EHR data. Key Features: Written based on hands-on experience of
contributors from multidisciplinary EHR research projects, which
include methods and approaches from statistics, computing,
informatics, data science and clinical/epidemiological domains.
Documents the detailed experience on EHR data extraction, cleaning
and preparation Provides a broad view of statistical approaches and
machine learning prediction models to deal with the challenges and
limitations of EHR data. Considers the complete cycle of EHR data
analysis. The use of EHR/EMR analysis requires close collaborations
between statisticians, informaticians, data scientists and
clinical/epidemiological investigators. This book reflects that
multidisciplinary perspective.
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