Evidence map›Paper›PMID 41424637›Full record

ArticlePaediatrics & child health2025

The use of artificial intelligence in paediatric postgraduate medical education: A scoping review.

Ajantha Nadarajah, Ghazal Malekzadeh, Savithiri Ratnapalan

Abstract read
In one paragraph

Article in Paediatrics & child health, 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

3 authors.

Ajantha NadarajahFaculty of Medicine, University of Toronto, Toronto, Ontario, Canada.
Ghazal MalekzadehDepartment of Biology, York University, Toronto, Ontario, Canada.
Savithiri RatnapalanFaculty of Medicine, University of Toronto, Toronto, Ontario, Canada.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Artificial intelligence (AI) encompasses a wide range of technologies that enable computers to mimic human intellect and is playing a significant role in healthcare education. Objectives: To review the current applications of AI in paediatric postgraduate medical education programs. Methods: A scoping review was conducted using a comprehensive literature search involving Ovid MEDLINE, Ovid Embase, and ERIC conducted from 1946 to May 27, 2024. Inclusion criteria involved articles that discussed AI in postgraduate paediatric education. Articles that addressed undergraduate education and other health professional education were excluded. Results: Nine articles met the inclusion criteria. Four studies were conducted in the United States, two in China, and one each in France, Korea, and Canada. The studies discussed the use of AI in general paediatrics, paediatric oncology, developmental paediatrics, and paediatric genetics. AI was used as a clinical decision support tool in postgraduate training in seven studies with mixed results on the accuracy of AI predictions. One study used AI models to assess residents' intubation competency, and another assessed the experiences and general perspectives of AI among paediatric residents and junior faculty. Conclusions: Amongst included studies, AI was largely used as a clinical decision support tool in paediatric postgraduate education and the accuracy of AI predictions are improved when large amounts of data are used to train and tune the AI model. As such, physicians should be trained in AI use and take an active role in training and tuning AI models on an ongoing basis to ensure appropriate use of AI in healthcare.

Indexed as

Artificial intelligenceMedical educationPaediatrics

Identifiers

PMID41424637
PMCPMC12718058

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.