Feasibility of Reidentifying Individuals in Large National Physical Activity Data Sets From Which Protected Health Information Has Been Removed With Use of Machine Learning

Abstract

This cross-sectional study of National Health and Nutrition Examination Survey data sets evaluates the feasibility of reidentifying accelerometer-measured physical activity data that have had protected health information removed, using support vector machines and random forest methods from machine learning.

Promises of Big Data and Artificial Intelligence in Nephrology and Transplantation

“…Despite having numerous imperfections, big data, as well as artificial intelligence have been applied in the field of medication from numerous parts [115,116]. There are numerous possible guidelines of using big data and artificial intelligence in nephrology that requires greater attention, as well as further consideration [74,78,[117][118][119][120][121][122][123][124][125].…”

Clinical Data: Sources and Types, Regulatory Constraints, Applications

“…Recognizing the need to respect and protect patient privacy, numerous regulations have been established to govern the use of clinical data by researchers, including the federal Health Insurance Portability and Accountability Act of 1996 (HIPAA) and the European Union General Data Protection Regulation. Institution‐specific guidelines and governing bodies such as institutional review boards (IRBs) also address research involving patient data and other sensitive data available in electronic medical records (e.g., administrative data), in part as a result of concerns regarding the liability of healthcare providers and institutions …”

Artificial Intelligence in Radiology—Ethical Considerations

“…However, real anonymization is more complicated than most people imagine. It has been written that "Entities facile with manipulating massive data can likely re-identify just about any radiology exam" [13]. Even fully anonymized datasets may be manipulatable in a manner that would allow their source to be identified; application of facial recognition software to 3D reconstructions of head and neck imaging can restore identification [14].…”