Evidence map›Paper›PMID 42387654›Full record

ReviewTropical diseases, travel medicine and vaccines2026

Balancing innovation and risk: artificial intelligence in travel medicine.

Perry J J van Genderen

Abstract readReview
In one paragraph

Review in Tropical diseases, travel medicine and vaccines, 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

1 author.

Perry J J van GenderenExpertise Centre Travel Risk Management, Corporate Travel Clinic, Maasboulevard 148, Rotterdam, The Netherlands. pjjvangenderen@travelclinic.com.ORCID http://orcid.org/0000-0001-9272-752X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Artificial intelligence (AI) is increasingly influencing travel medicine, a field traditionally reliant on expert judgement and static guidelines. Machine learning systems, generative AI models and digital surveillance tools have the potential to enhance pre-travel counselling, improve diagnostic pathways and strengthen outbreak detection. However, concerns remain regarding variable performance, data privacy and the absence of clear regulatory frameworks. This Perspective examines the role of AI across the travel health continuum, highlighting both opportunities and limitations. Rather than replacing clinical expertise, AI should be carefully validated and integrated to support decision-making. Responsible implementation could improve access, personalize care and strengthen global health security.

Indexed as

Artificial intelligenceDigital healthGlobal healthSurveillanceTelemedicineTravel medicine

Identifiers

PMID42387654
PMCPMC13321647

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.