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ChatGPT-4o generates neonatal resus scenarios

Feasibility and challenges of large language model (LLM)-generated neonatal resuscitation simulations: a multicenter exploratory study
Scandinavian Journal of Trauma, Resuscitation and Emergency Medicine · Added 26 May 2026

This prospective multicenter pilot tested whether ChatGPT-4o and DeepSeek-R1 could generate valid neonatal resuscitation simulation scenarios for training, finding ChatGPT-4o performed comparably to official NRP scenarios in overall quality while demonstrating strengths in debriefing design but having gaps in dynamic vital sign provision.

Study type

Other

Design

Prospective multicentre pilot study

Participants

16 simulation scenarios rated by 9 blinded instructors from 5 centres

Main finding

ChatGPT-4o scenarios scored comparably to NRP® scenarios overall, with higher debriefing design scores (r=0.25, P=0.02); DeepSeek and RETAIN scored lower overall, and ChatGPT showed gaps in dynamic vital sign provision.

Caveat

Pilot study with only instructor ratings, no learner outcomes

Bottom line

Hypothesis-generating

Learning goal

Weigh the value of AI-generated simulation scenarios against conventional resources when designing neonatal resuscitation training.

More

• Topic: Education & training
• Daily scan: 26 May 2026

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