ArticleNature communications2021
Truly privacy-preserving federated analytics for precision medicine with multiparty homomorphic encryption.
Article in Nature communications, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 81 papers, 1 of them a synthesis that pooled it.
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
81 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Safeguarding biomedical AI: a critical scoping review of privacy-enhancing technologies, hybrid approaches, and deployment models.Frontiers in digital health · 2026Pooled it
- Privacy and Security Throughout the Health Data Life Cycle: From Primary Care to Research Networks.Annual review of biomedical data science · 2026Review
- Federated generative prompt learning with vision foundation models: universal efficient multi-center medical image analysis.NPJ digital medicine · 2026Article
- A multiparty homomorphic encryption approach to confidential federated Kaplan-Meier survival analysis.NPJ digital medicine · 2026Article
- Biobanked Liver Organoids: A Roadmap for Precision Hepatology.BioEssays : news and reviews in molecular, cellular and developmental biology · 2026Review
- Secure bioinformatics: privacy-preserving federated analytics using homomorphic encryption.Bioinformatics (Oxford, England) · 2026Article
- WiNGS-API: a federated genome/phenome data sharing platform enabling gene discovery and variant classification for rare diseases.Genome medicine · 2026Article
- Precision cardiovascular medicine with big data and AI.NPJ digital medicine · 2026Review
- AI and Big Data in Oncology: A Physician-Centered Perspective on Emerging Clinical and Research Applications.Cancer innovation · 2026Review
- NitroGene: privacy-preserving collaborative genomic analysis using AWS nitro enclaves.Bioinformatics advances · 2026Article
- Bioinks in systems biology: integrating biomaterial design with cellular network modelling for predictive biofabrication.Frontiers in bioengineering and biotechnology · 2026Review
- PP-GWAS: Privacy Preserving Multi-Site Genome-wide Association Studies.Nature communications · 2025Article
- Data visiting governance: a conceptual framework.Human genomics · 2025Review
- PRISM: privacy-preserving rare disease analysis using fully homomorphic encryption.Bioinformatics (Oxford, England) · 2025Article
- Integration of Multi-Modal Biosensing Approaches for Depression: Current Status, Challenges, and Future Perspectives.Sensors (Basel, Switzerland) · 2025Review
- Shechi: A Secure Distributed Computation Compiler Based on Multiparty Homomorphic Encryption.Proceedings. UNIX Security Symposium · 2025Article
- Making the case for an International Childhood Cancer Data Partnership.Journal of the National Cancer Institute · 2025Article
- Medical laboratory data-based models: opportunities, obstacles, and solutions.Journal of translational medicine · 2025Review
- Judged by your neighbors: A novel framework for personalized assessment of brain structural aging effects in diverse populations.medRxiv : the preprint server for health sciences · 2025Article
- Communication-efficient federated learning of temporal effects on opioid use disorder with data from distributed research networks.Journal of the American Medical Informatics Association : JAMIA · 2025Article
21 more citing papers are in PubMed but not listed here.
Corrections and comments
- Erratum issued
Authors and funding
9 authors.
Funding
Abstract
Using real-world evidence in biomedical research, an indispensable complement to clinical trials, requires access to large quantities of patient data that are typically held separately by multiple healthcare institutions. We propose FAMHE, a novel federated analytics system that, based on multiparty homomorphic encryption (MHE), enables privacy-preserving analyses of distributed datasets by yielding highly accurate results without revealing any intermediate data. We demonstrate the applicability of FAMHE to essential biomedical analysis tasks, including Kaplan-Meier survival analysis in oncology and genome-wide association studies in medical genetics. Using our system, we accurately and efficiently reproduce two published centralized studies in a federated setting, enabling biomedical insights that are not possible from individual institutions alone. Our work represents a necessary key step towards overcoming the privacy hurdle in enabling multi-centric scientific collaborations.
Indexed as
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.