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Discover how data analytics and machine and deep learning tools can clean data and uncover insights to complete hospital equipment work orders more efficiently.
HealthCareBusiness News, June 11, 2019
By John Fischer
Data scientists spend most of their time cleaning data. With over 230 million work orders in healthcare, they need to lean on various tools to analyze the data and make it useful to generate results.
In the article, Understanding "Data Cleaning" in Equipment Service, and the Tools Use to Do It, you will hear from Michael Garel, Accruent's director of data strategy. He will explain the advantages of applying data science to clean up data to ensure faster completion of work orders for workflows and quality patient care. He will also highlight specific use cases for using data analytics, machine learning, and deep learning.
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