Machine Learning for Medical Coding in Healthcare Surveys.

Christine A Lucas, Emily Hadley, Robert Chew, Jason Nance, Peter Baumgartner, Rita Thissen, David M Plotner, Christine Carr, Aerian Tatum
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引用次数: 0

Abstract

Objectives Medical coding, or the translation of healthcare information into numeric codes, is expensive and time intensive. This exploratory study evaluates the use of machine learning classifiers to perform automated medical coding for large statistical healthcare surveys.

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医疗保健调查中医疗编码的机器学习。
医学编码,或将医疗保健信息转换为数字代码,既昂贵又耗时。本探索性研究评估了机器学习分类器在大型统计医疗调查中执行自动医疗编码的使用。
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来源期刊
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2.50
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期刊介绍: Reports describing the general programs of the National Center for Health Statistics and its offices and divisions and the data collection methods used. Series 1 reports also include definitions and other material necessary for understanding the data.
期刊最新文献
Plan and Operations of the National Health and Nutrition Examination Survey, August 2021-August 2023. Assessing Laboratory Method Validations for Informing Inference Across Survey Cycles in the National Health and Nutrition Examination Survey. Developing Sampling Weights for Statistical Analysis of Parent-Child Pair Data From the National Health Interview Survey. Validation of the Enhanced Opioid Identification and Co-occurring Disorders Algorithms. National Center for Health Statistics' 2019 Research and Development Survey, RANDS 3.
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