Evidence map›Paper›PMID 35772014›Full record

ArticleBiopreservation and biobanking2022

Leveraging Algorithms to Improve Decision-Making Workflows for Genomic Data Access and Management.

Vasiliki Rahimzadeh, Jonathan Lawson, Greg Rushton, Edward S Dove

Abstract read
In one paragraph

Article in Biopreservation and biobanking, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed, 1 pooled it
–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

7 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Toward ethical provenance tracking: The GA4GH model data access agreement (DAA).Genetics in medicine : official journal of the American College of Medical Genetics · 2026
    Article
  4. Article
  5. Article
  6. Article
  7. Review
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

4 authors.

Vasiliki RahimzadehStanford Center for Biomedical Ethics, Stanford University, Stanford, California, USA.ORCID 0000-0003-3537-7601
Jonathan LawsonBroad Institute of MIT and Harvard, Cambridge, Massachusetts, USA.
Greg RushtonStanford Center for Biomedical Ethics, Stanford University, Stanford, California, USA.
Edward S DoveSchool of Law, University of Edinburgh, Edinburgh, United Kingdom.

Funding

The Stanford Training Program in ELSI ResearchT32HG008953 · NHGRI · STANFORD UNIVERSITY · PI Mildred K. Cho, Meghan Halley · 2016 to 2026
$3.1M
NHGRI NIH HHS T32 HG008953
6 · The paper itself

Abstract

Studies on the ethics of automating clinical or research decision making using artificial intelligence and other algorithmic tools abound. Less attention has been paid, however, to the scope for, and ethics of, automating decision making within regulatory apparatuses governing the access, use, and exchange of data involving humans for research. In this article, we map how the binary logic flows and real-time capabilities of automated decision support (ADS) systems may be leveraged to accelerate one rate-limiting step in scientific discovery: data access management. We contend that improved auditability, consistency, and efficiency of the data access request

Indexed as

Artificial IntelligenceGenomicsHumansResearch PersonnelWorkflowautomated decision systemdata access committeeethicsgenomicshealth

Identifiers

PMID35772014
PMCPMC9603251

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.