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ABSTRACT. I develop a conceptual framework based on a systematic and comprehensive literature review on the relationship between machine learning-based natural language processing (NLP) algorithms and electronic health records data. Building my argument by drawing on data collected from 3M Health Information Systems, Maruti Techlabs, McKinsey, Mindfields, and TDWI, I performed analyses and made estimates regarding immediate benefits healthcare organizations can get by leveraging NLP (%, relevance). The data for this research were gathered via an online survey questionnaire and were analyzed through structural equation modeling on a sample of 4,200 respondents.

Keywords: electronic health record; machine learning; natural language processing

How to cite: Costea, Elena-Alexandra (2020). “Machine Learning-based Natural Language Processing Algorithms and Electronic Health Records Data,” Linguistic and Philosophical Investigations 19: 93–99. doi: 10.22381/LPI1920205

Received 1 January 2020 • Received in revised form 12 March 2020
Accepted 14 March 2020 • Available online 16 March 2020

Elena-Alexandra Costea
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The University of Bucharest, Romania

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