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Tutorial: Data-deidentification of Text in the Electronic Medical Records
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Tutorial: Data-deidentification of Text in the Electronic Medical Records

Last Updated on January 5, 2024 by Editorial Team

Author(s): Dr. Mandar Karhade, MD. PhD.

Originally published on Towards AI.

Data de-identification in Healthcare data is the biggest headache. Let's see how we can handle it

The tutorial starts in the middle of the article — so if you want to jump over the intro- Please jump over to the tutorial here- Cheers

Text anonymization plays a crucial role in safeguarding sensitive healthcare information, addressing the growing concern of privacy and confidentiality in the digital era. The sensitivity of patient information is so critical that it ends up blocking ways to advance the technology within the field. As the healthcare industry continues to embrace technological advancements, the need to protect patient data becomes increasingly paramount. In this article, we will explore the importance of text anonymization in healthcare and then follow it up with a hands-on tutorial on how to use it.

One of the primary reasons for the adoption of text anonymization in healthcare is to preserve patient privacy. Medical records contain a wealth of personal information, including sensitive details about an individual’s health history, treatments, and diagnoses. As the medical industry has outgrown its days of paper documents to digital format, the ability to share, transfer, and utilize data for various purposes has increased exponentially. However, that means that the risk of accidentally breaching the trust between a physician and a patient is high, too. The… Read the full blog for free on Medium.

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