Text mining analysis of over 392 million compromised healthcare records

• Autorzy: Koczkodaj Waldemar W. , Nowacki Marek , Pedrycz Witold , Strzałka Dominik

Identyfikatory

DOI

10.12913/22998624/195690

• Języki publikacji: EN

Abstrakty

EN

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.

Słowa kluczowe

EN

data security; text mining; AI; latent dirichlet allocation; elbow method; text coherence; perplexity measure

• Wydawca: Lublin University of Technology ; Polish Society of Ecological Engineering (PTIE), Branch of PTIE in Lublin
• Czasopismo: Advances in Science and Technology. Research Journal
• Rocznik: 2025
• Tom: Vol. 19, no. 2
• Strony: 73--81
• Opis fizyczny: Bibliogr. 50 poz., fig., tab.

Twórcy

autor

Koczkodaj Waldemar W.

• Laurentian University, 935 Ramsey Lake Rd, Sudbury, ON P3E 2C6, Canada

• https://orcid.org/0000-0002-6981-7698

autor

Nowacki Marek

• WSB Merito University in Poznań, ul. Powstańców Wielkopolskich 5, 61-895 Poznań, Poland

• https://orcid.org/0000-0002-6981-7698

autor

Pedrycz Witold

• University of Alberta, 116 St & 85 Ave, Edmonton, AB T6G 2R3, Canada

• https://orcid.org/0000-0002-9335-9930

autor

Strzałka Dominik

• Rzeszów University of Technology, Al. Powstańców Warszawy 12, 35-959 Rzeszów, Poland

• https://orcid.org/0000-0002-8887-4321

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Uwagi

Opracowanie rekordu ze środków MNiSW, umowa nr POPUL/SP/0154/2024/02 w ramach programu "Społeczna odpowiedzialność nauki II" - moduł: Popularyzacja nauki (2025).