Evidence map›Paper›PMID 37351796›Full record

ArticleAMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science2023

Efficient Federated Kinship Relationship Identification.

Xinyue Wang, Leonard Dervishi, Wentao Li, Xiaoqian Jiang, Erman Ayday, Jaideep Vaidya

Abstract read
In one paragraph

Article in AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from 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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Xinyue WangRutgers University, Newark, NJ.
Leonard DervishiCase Western Reserve University, Cleveland, OH.
Wentao LiUTHealth, Houston, TX.
Xiaoqian JiangUTHealth, Houston, TX.
Erman AydayCase Western Reserve University, Cleveland, OH.
Jaideep VaidyaRutgers University, Newark, NJ.

Funding

Supplement for high performance compute clustersR35GM134927 · NIGMS · RUTGERS THE STATE UNIV OF NJ NEWARK · PI VAIDYA, JAIDEEP · 2020 to 2024
$2.1M
NIGMS NIH HHS R35 GM134927
6 · The paper itself

Abstract

Kinship relationship estimation plays a significant role in today's genome studies. Since genetic data are mostly stored and protected in different silos, retrieving the desirable kinship relationships across federated data warehouses is a non-trivial problem. The ability to identify and connect related individuals is important for both research and clinical applications. In this work, we propose a new privacy-preserving kinship relationship estimation framework: Incremental Update Kinship Identification (INK). The proposed framework includes three key components that allow us to control the balance between privacy and accuracy (of kinship estimation): an incremental process coupled with the use of auxiliary information and informative scores. Our empirical evaluation shows that INK can achieve higher kinship identification correctness while exposing fewer genetic markers.

Identifiers

PMID37351796
PMCPMC10283133

What OpenQuestion holds

Textmetadata
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Registered trials

None linked

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.