ArticleScience advances2021
Re-identification of individuals in genomic datasets using public face images.
Article in Science advances, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
19 citing papers in PubMed.
- Artificial intelligence in hepatocellular carcinoma diagnosis and AI-assisted treatment support: Current landscape and future directions.Liver research (Beijing, China) · 2026Review
- A Bilayer Feature Fusion Framework for Pan-Cancer Survival Prediction Based on Multihead Attention and Adaptive Differential Privacy: Model Development and Validation Study.JMIR medical informatics · 2026Article
- The Portuguese Beacon: sharing genomic variant data safely.Database : the journal of biological databases and curation · 2026Article
- Advancing genome-based precision medicine: a review on machine learning applications for rare genetic disorders.Briefings in bioinformatics · 2025Review
- A decade of research on genetic privacy: the findings of the GetPreCiSe Center at Vanderbilt University.Frontiers in genetics · 2025Review
- Genomic privacy and security in the era of artificial intelligence and quantum computing.Discover computing · 2025Review
- Revolutionizing Cancer Registries: The Promise and Challenges of Integrating Molecular Markers for Enhanced Patient Care and Research.Journal of registry management · 2025Article
- Legal aspects of privacy-enhancing technologies in genome-wide association studies and their impact on performance and feasibility.Genome biology · 2024Review
- An Ethical Approach to Genomic Privacy Preserving Technology Development.Proceedings. IEEE International Conference on Healthcare Informatics · 2024Article
- Assessing Privacy Vulnerabilities in Genetic Data Sets: Scoping Review.JMIR bioinformatics and biotechnology · 2024Article
- Article
- Future-proofing genomic data and consent management: a comprehensive review of technology innovations.GigaScience · 2024Review
- A synthetic data set to benchmark anti-money laundering methods.Scientific data · 2023Article
- Enabling tradeoffs in privacy and utility in genomic data Beacons and summary statistics.Genome research · 2023Article
- Multimodal analysis methods in predictive biomedicine.Computational and structural biotechnology journal · 2023Review
- Decoding the Human Face: Progress and Challenges in Understanding the Genetics of Craniofacial Morphology.Annual review of genomics and human genetics · 2022Review
- Sociotechnical safeguards for genomic data privacy.Nature reviews. Genetics · 2022Review
- Article
- Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
Abstract
Recent studies suggest that genomic data can be matched to images of human faces, raising the concern that genomic data can be re-identified with relative ease. However, such investigations assume access to well-curated images, which are rarely available in practice and challenging to derive from photos not generated in a controlled laboratory setting. In this study, we reconsider re-identification risk and find that, for most individuals, the actual risk posed by linkage attacks to typical face images is substantially smaller than claimed in prior investigations. Moreover, we show that only a small amount of well-calibrated noise, imperceptible to humans, can be added to images to markedly reduce such risk. The results of this investigation create an opportunity to create image filters that enable individuals to have better control over re-identification risk based on linkage.
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.