Evidence map›Paper›PMID 37796364›Full record

ArticleJournal of community genetics2024

Ethics of artificial intelligence in prenatal and pediatric genomic medicine.

Simon Coghlan, Christopher Gyngell, Danya F Vears

Abstract read
In one paragraph

Article in Journal of community genetics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
13citing 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

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

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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

3 authors.

Simon CoghlanSchool of Computing and Information Systems (CIS), Centre for AI and Digital Ethics (CAIDE), The University of Melbourne, Grattan St, Melbourne, Victoria, 3010, Australia. simon.coghlan@unimelb.edu.au.ORCID https://orcid.org/0000-0002-6021-9878
Christopher GyngellBiomedical Ethics Research Group, Murdoch Children's Research Institute, The Royal Children's Hospital, 50 Flemington Rd, Parkville, Victoria, 3052, Australia.
Danya F VearsBiomedical Ethics Research Group, Murdoch Children's Research Institute, The Royal Children's Hospital, 50 Flemington Rd, Parkville, Victoria, 3052, Australia.ORCID https://orcid.org/0000-0002-6290-545X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This paper examines the ethics of introducing emerging forms of artificial intelligence (AI) into prenatal and pediatric genomic medicine. Application of genomic AI to these early life settings has not received much attention in the ethics literature. We focus on three contexts: (1) prenatal genomic sequencing for possible fetal abnormalities, (2) rapid genomic sequencing for critically ill children, and (3) reanalysis of genomic data obtained from children for diagnostic purposes. The paper identifies and discusses various ethical issues in the possible application of genomic AI in these settings, especially as they relate to concepts of beneficence, nonmaleficence, respect for autonomy, justice, transparency, accountability, privacy, and trust. The examination will inform the ethically sound introduction of genomic AI in early human life.

Indexed as

Artificial intelligence (AI)ChildrenEthicsGenomicsPediatricsPrenatal medicine

Identifiers

PMID37796364
PMCPMC10857992

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.