Text mining analysis of over 392 million compromised healthcare records

The U.S. Department of health and human services (HHS) and the Office for Civil Rights (OCR) enforce federal civil rights laws.This study analyzed the collected data on healthcare data breaches, which affected over 392 million records in the USA from 21 October 2009 until 19 April 2024, using text mining.Using Latent Dirichlet allocation (LDA) and the Elbow methods, five major topics for text mining analysis were established.The analysis allowed to identify key breach reasons for targeting effective remedial actions and increasing data security awareness.

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Publication Details

Journal
Advances in Science and Technology – Research Journal
Published
2024-11-07
DOI
https://doi.org/10.12913/22998624/195690
Citations
3
Primary Topic
Artificial Intelligence in Healthcare
Type
article
Field-Weighted Citation Impact
2.12
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article

Text mining analysis of over 392 million compromised healthcare records

Waldemar W. Koczkodaj, Dominik Strzałka, Marek Nowacki, Witold Pedrycz
3 citations
Advances in Science and Technology – Research Journal
Artificial Intelligence in Healthcare
2.12
article

Text mining analysis of over 392 million compromised healthcare records

Waldemar W. Koczkodaj, Dominik Strzałka, Marek Nowacki, Witold Pedrycz
article en
3 citations

Abstract

The U.S. Department of health and human services (HHS) and the Office for Civil Rights (OCR) enforce federal civil rights laws.This study analyzed the collected data on healthcare data breaches, which affected over 392 million records in the USA from 21 October 2009 until 19 April 2024, using text mining.Using Latent Dirichlet allocation (LDA) and the Elbow methods, five major topics for text mining analysis were established.The analysis allowed to identify key breach reasons for targeting effective remedial actions and increasing data security awareness.

Advances in Science and Technology – Research JournalVol. 19(2)
Decent work and economic growth
Openalex Percentile: Top 9%
Artificial Intelligence in Healthcare
2.12
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