Big healthcare data: preserving security and privacy
By Karim Abouelmehdi, Abderrahim Beni Hssane, Hayat Khaloufi. Journal of Big Data, 2018
588 citations recorded by the source corpus.
Big data has fundamentally changed the way organizations manage, analyze and leverage data in any industry. One of the most promising fields where big data can be applied to make a change is healthcare. Big healthcare data has considerable potential to improve patient outcomes, predict outbreaks of epidemics, gain valuable insights, avoid preventable diseases, reduce the cost of healthcare delivery and improve the quality of life in general. However, deciding on the allowable uses of data while preserving security and patient’s right to privacy is a difficult task. Big data, no matter how useful for the advancement of medical science and vital to the success of all healthcare organizations, can only be used if security and privacy issues are addressed. To ensure a secure and trustworthy big data environment, it is essential to identify the limitations of existing solutions and envision directions for future research. In this paper, we have surveyed the state-of-the-art security and privacy challenges in big data as applied to healthcare industry, assessed how security and privacy issues occur in case of big healthcare data and discussed ways in which they may be addressed. We mainly focused on the recently proposed methods based on anonymization and encryption, compared their strengths and limitations, and envisioned future research directions.
Subfields: Artificial Intelligence, Information Systems
View Paper: https://www.semanticscholar.org/paper/4b4b63405efd22a96cc45b22c08124d62a475d6f
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In Artificial Intelligence
Citations in the corpus
- Fairness of artificial intelligence in healthcare: review and recommendations (2023, background): “Protecting data storage and transmission is an important aspect of data privacy [98].”
- Addressing bias in big data and AI for health care: A call for open science (2021, background): “Although health care data are necessary to advance medicine, they contain sensitive information that needs to be safeguarded for privacy reasons.(54) It is not enough to simply code the name and surname of a patient to ensure anonymity.”
- AI in Medical Imaging Informatics: Current Challenges and Future Directions (2020, unknown): “Keeping up with storage, sharing, and processing while preserving privacy and anonymity [258], [259], has pushed boundaries in traditional means of doing research.”
- The use of Big Data Analytics in healthcare (2022, background): “…data represents a huge potential for the transformation of healthcare: improvement of patients’ results, prediction of outbreaks of epidemics, valuable insights, avoidance of preventable diseases, reduction of the cost of healthcare delivery and improvement of the quality of life in general [1].”