  Daily, massive volume of data are produced due to the internet of things'
rapid development, which has now permeated the healthcare industry. Recent
advances in data mining have spawned a new field of a study dubbed
privacy-preserving data mining (PPDM). PPDM technique or approach enables the
extraction of actionable insight from enormous volume of data while
safeguarding the privacy of individual information and benefiting the entire
society Medical research has taken a new course as a result of data mining with
healthcare data to detect diseases earlier and improve patient care. Data
integration necessitates the sharing of sensitive patient information. However,
substantial privacy issues are raised in connection with the storage and
transmission of potentially sensitive information. Disclosing sensitive
information infringes on patients' privacy. This paper aims to conduct a review
of related work on privacy-preserving mechanisms, data protection regulations,
and mitigating tactics. The review concluded that no single strategy
outperforms all others. Hence, future research should focus on adequate
techniques for privacy solutions in the age of massive medical data and the
standardization of evaluation standards.
