ArticleProceedings of the ... International World-Wide Web Conference. International WWW Conference2021
Communication Efficient Federated Generalized Tensor Factorization for Collaborative Health Data Analytics.
Article in Proceedings of the ... International World-Wide Web Conference. International WWW Conference, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
What it found
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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.
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Who cites it
9 citing papers in PubMed.
- Cross-silo Federated Learning with Record-level Personalized Differential Privacy.Conference on Computer and Communications Security : proceedings of the ... conference on computer and communications security. ACM Conference on Computer and Communications Security · 2024Article
- Recent methodological advances in federated learning for healthcare.Patterns (New York, N.Y.) · 2024Review
- Creating High-Quality Synthetic Health Data: Framework for Model Development and Validation.JMIR formative research · 2024Article
- Federated Learning in Healthcare: A Benchmark Comparison of Engineering and Statistical Approaches for Structured Data Analysis.Health data science · 2024Article
- Federated and distributed learning applications for electronic health records and structured medical data: a scoping review.Journal of the American Medical Informatics Association : JAMIA · 2023Article
- A Review of Privacy Enhancement Methods for Federated Learning in Healthcare Systems.International journal of environmental research and public health · 2023Review
- Federated Learning in Health care Using Structured Medical Data.Advances in kidney disease and health · 2023Review
- Communication Efficient Tensor Factorization for Decentralized Healthcare Networks.Proceedings. IEEE International Conference on Data Mining · 2021Article
- Review
Corrections and comments
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Authors and funding
5 authors.
Funding
Abstract
Modern healthcare systems knitted by a web of entities (e.g., hospitals, clinics, pharmacy companies) are collecting a huge volume of healthcare data from a large number of individuals with various medical procedures, medications, diagnosis, and lab tests. To extract meaningful medical concepts (i.e., phenotypes) from such higher-arity relational healthcare data, tensor factorization has been proven to be an effective approach and received increasing research attention, due to their intrinsic capability to represent the high-dimensional data. Recently, federated learning offers a privacy-preserving paradigm for collaborative learning among different entities, which seemingly provides an ideal potential to further enhance the tensor factorization-based collaborative phenotyping to handle sensitive personal health data. However, existing attempts to federated tensor factorization come with various limitations, including restrictions to the classic tensor factorization, high communication cost and reduced accuracy. We propose a
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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.