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Enhancing Privacy in Healthcare Research: Leveraging Blockchain and Generative Language Models in Biostatistics

EasyChair Preprint no. 12553

11 pagesDate: March 18, 2024

Abstract

Privacy concerns in healthcare research have prompted the exploration of innovative solutions to securely manage and analyze sensitive patient data. This paper proposes a novel approach that leverages blockchain technology and generative language models in biostatistics to enhance privacy while facilitating data analysis. By employing blockchain's immutable ledger and smart contract functionalities, along with generative language models' ability to synthesize data, this framework ensures data privacy, integrity, and accessibility. Through a case study, we demonstrate the feasibility and effectiveness of our approach in maintaining privacy while enabling meaningful statistical analyses in healthcare research.

Keyphrases: Biostatistics, Blockchain Technology, Data Security, Generative Language Models, Healthcare research, Privacy

BibTeX entry
BibTeX does not have the right entry for preprints. This is a hack for producing the correct reference:
@Booklet{EasyChair:12553,
  author = {William Jack},
  title = {Enhancing Privacy in Healthcare Research: Leveraging Blockchain and Generative Language Models in Biostatistics},
  howpublished = {EasyChair Preprint no. 12553},

  year = {EasyChair, 2024}}
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