6 Tips for choosing a natural language processing solution

Written by: Anand Shroff

The digitization in health care has resulted in an abundance of data, and many are grappling with how best to manage and use the data to their advantage. An added challenge in health care data is that much of the most valuable information is in the form of unstructured data, primarily in physicians’ clinical notes inside patients’ medical records.

Historically, analyzing this data has required a human touch—individuals reading through medical records and manually extracting information from the data. Of course, this is incredibly resource-intensive and error-prone, no doubt leaving errors and other mistakes undetected among the sheer volume of records.

Natural language processing (NLP) has emerged as a way to streamline the analysis of that unstructured data, dramatically improving both the speed and accuracy with which health care organizations can turn their big data into smart data. Here’s how leveraging NLP technology can help improve efficiency in data analysis and what to look for when choosing a solution.

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