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When artificial intelligence protects privacy, it can be the path to better healthcare

Insight into health data can change the rules of the game for research and patient care, but the road ahead is not without obstacles. The desire to leverage health data to provide better treatment and use of resources often clashes with strict rules on the use of health data. Fortunately, privacy-enhancing technologies open the door to secure and efficient analysis of health data.

(Illustration photo from Colourbox)
(Illustration photo from Colourbox)

A new research report from the Norwegian Centre for E-health Research presents two privacy-enhancing technologies, federated learning and synthetic data, and explores how they can solve the challenge of accessing high-quality health data in sufficient quantity for research and service development.

Health data: strictly guarded goldmine

Healthcare produces huge amounts of data. If we use this information correctly, it can aid research, improve diagnostics and ensure that we use healthcare resources in a smart way. Artificial intelligence (AI), especially machine learning, has proven to be a powerful tool for analyzing large amounts of healthcare data quickly and efficiently.

Health data is not only valuable - it's also sensitive, and its use is highly regulated. It is difficult to access health data for secondary use.

- Ensuring that privacy and data security rules are followed takes a lot of time and effort. This is a major challenge when it comes to accessing training data and spreading the use of AI in healthcare. Privacy-enhancing technologies can help to collect, process, analyze and share data while ensuring data security and privacy, says Alexandra Makhlysheva, Senior Advisor in the Department of Health Data and Analytics at the Norwegian Centre for E-health Research. She is one of the authors of the report.