Analyzing the Data Completeness of Patients’ Records Using a Random Variable Approach to Predict the Incompleteness of Electronic Health Records

Analyzing the Data Completeness of Patients’ Records Using a Random Variable Approach to Predict the Incompleteness of Electronic Health Records

The purpose of this article is to illustrate an investigation of methods that can be effectively used to predict the data incompleteness of a dataset. Here, the investigators have conceptualized data incompleteness as a random variable, with the overall goal behind experimentation providing a 360-de...

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Bibliographic Details
Main Authors: Varadraj P. Gurupur, Paniz Abedin, Sahar Hooshmand, Muhammed Shelleh
Format: Article
Language:English
Published: MDPI AG 2022-10-01
Series:Applied Sciences
Subjects:
health informatics
big data models
data completeness
probability density
Kolomogorov–Smirnov test
Online Access:https://www.mdpi.com/2076-3417/12/21/10746

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