Evidence map›Paper›PMID 42620986›Full record

ReviewBioscience2026

Leveraging artificial intelligence to enhance marine biosecurity.

Marnie L Campbell, Chi T U Le, Jumana Abu-Khalaf, Craig D H Sherman

Abstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in Bioscience, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Marnie L CampbellSchool of Science, Edith Cowan University, 270 Joondalup Drive, Joondalup, WA 6027, Australia.
Chi T U LeSchool of Science, Edith Cowan University, 270 Joondalup Drive, Joondalup, WA 6027, Australia.ORCID https://orcid.org/0000-0003-3554-2777
Jumana Abu-KhalafSchool of Science, Edith Cowan University, 270 Joondalup Drive, Joondalup, WA 6027, Australia.
Craig D H ShermanSchool of Life and Environmental Science, Deakin University, 75 Pigdons Rd, Waurn Ponds, VIC 3216, Australia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Marine biosecurity stands at the crossroads of innovation and necessity, with artificial intelligence (AI) offering promising tools to enhance risk assessment, surveillance, and response strategies for invasive species management. Despite the rapid growth of AI applications in marine science, there has been no comprehensive overview of its potential role in enhancing and supporting marine biosecurity. Our literature review aims to fill this gap, showing that AI use in this field remains limited and underdeveloped. Through our literature analysis, we identify key opportunities for AI research and innovation across the marine biosecurity continuum, while also highlighting both general and domain-specific challenges. We conclude by proposing a roadmap to guide the responsible development and implementation of AI in marine biosecurity.

Indexed as

global collaborationinclusive and equitable AIinnovation in marine pest managementmarine ecosystem protectionnon-native marine species

Identifiers

PMID42620986
PMCPMC13486004

What OpenQuestion holds

Textmetadata
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.