Survey On Health Data Privacy Preserving Techniques and Features
MRS. RITU RAIKWAR
, DR. MANMOHAN SINGH
Data Mining, Healthcare Records, Information Extraction, Association Rule.
The primary objective of Data Mining is to extract knowledge from vast datasets. This involves the application
of data mining techniques to uncover meaningful information and patterns within extensive databases. In the realm of
health science, machine learning has become increasingly indispensable, leveraging its ability to derive valuable insights
from high-dimensional data. However, this often necessitates the amalgamation of research and patient data from various
institutions and hospitals—a challenging feat due to privacy constraints. In a recent survey, the paper explores
methodologies proposed by different researchers, delving into data mining methods that aid in information extraction.
The paper also discusses features employed by these approaches to address data privacy concerns. Furthermore, it
elaborates on various data mining techniques and provides a comprehensive examination of evaluation parameters for
comparing privacy-preserving methods.
"Survey On Health Data Privacy Preserving Techniques and Features", IJSDR - International Journal of Scientific Development and Research (www.IJSDR.org), ISSN:2455-2631, Vol.10, Issue 9, page no.a733-a736, September-2025, Available :https://ijsdr.org/papers/IJSDR2509088.pdf
Volume 10
Issue 9,
September-2025
Pages : a733-a736
Paper Reg. ID: IJSDR_304944
Published Paper Id: IJSDR2509088
Downloads: 00059
Research Area: Science All
Country: BHOPAL, MADHYA PRADESH, India
ISSN: 2455-2631 | IMPACT FACTOR: 9.15 Calculated By Google Scholar | ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 9.15 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator
Publisher: IJSDR(IJ Publication) Janvi Wave
