Evidence map›Paper›PMID 42304990›Full record

SynthesisZhongguo dang dai er ke za zhi = Chinese journal of contemporary pediatrics2026

[Empowering narrative medicine with artificial intelligence: a new perspective in pediatric medical education].

Zhen-Ai Jin, Ru-Lan Dai

Abstract readSystematic ReviewEnglish Abstract
In one paragraph

Synthesis in Zhongguo dang dai er ke za zhi = Chinese journal of contemporary pediatrics, 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

2 authors.

Zhen-Ai JinPerinatal/Neonatal Clinic and Children's Family Clinic & Narrative Medicine Research Lab, Yanbian University Hospital, Yanji, Jilin 133000, China.
Ru-Lan Dai

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This paper systematically explores the integration pathways, challenges, and future directions of artificial intelligence (AI) technology and narrative medicine in pediatric medical education. Due to the unique characteristics of the pediatric population, pediatric diagnosis and treatment place higher demands on physicians' empathy, communication skills, and humanistic qualities. Narrative medicine, as a key paradigm to address deficiencies in medical humanities, provides a theoretical framework and practical methods for cultivating these core humanistic qualities. However, its teaching promotion and practice face challenges such as insufficient scaling, lack of standardization, and limited depth of feedback. Advances in AI technology, particularly in natural language processing and generative AI, offer new opportunities to overcome these challenges. Based on a systematic literature review, relevant theories, research methods, and practical outcomes of the integration between AI and narrative medicine are synthesized, and a three-stage integration model of "independent development - skill empowerment - collaborative deepening" is constructed. The integration process faces significant challenges including technical ethics, educational integration, and value alienation. Finally, a new paradigm for future pediatric medical education centered on "human-machine collaboration" is proposed, aiming to cultivate the next generation of pediatricians who possess excellent technical skills, profound empathy, and resilient professional spirit, thereby opening new perspectives.

Indexed as

Artificial IntelligenceEducation, MedicalNarrative MedicinePediatricsGenerative Artificial IntelligenceHumansArtificial intelligenceLarge language modelMedical humanitiesNarrative medicinePediatric medical education

Identifiers

PMID42304990
PMCPMC13273474

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.