Evidence map›Paper›PMID 41313195›Full record

ArticleJMIR formative research2025

Evaluating the Role of Artificial Intelligence in Breast Self-Examination.

Shirish Nayyar

Abstract read
In one paragraph

Article in JMIR formative research, 2025. 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.

Shirish NayyarGeneral Internal Medicine, King's College Hospital NHS Foundation Trust, Denmark Hill, London, SE59RS, United Kingdom, 44 7342262402.ORCID 0009-0003-6983-5356

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Unlabelled: This viewpoint explores the role of conversational artificial intelligence (AI) in educating the public on breast self-examination, using an interaction with DeepSeek AI as an example, where 6 AI-generated responses to commonly asked questions were compared with guidelines published by organizations such as the World Health Organization. Although the AI provided clear, accessible, and evidence-aligned responses consistent with professional guidance, limitations included oversimplification and absence of multimedia resources. These findings suggest that AI can support public health education but should be complemented by physician oversight and evidence-based resources for responsible use.

Indexed as

Artificial IntelligenceBreast NeoplasmsBreast Self-ExaminationHealth EducationFemaleHumansAIartificial intelligencebreastbreast cancercancerDeepSeekself assessment

Identifiers

PMID41313195
PMCPMC12661592

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.