Performance of a Large Language Model on Practice Questions for the Neonatal Board Examination-Reference-Cited by-同舟云学术

Performance of a Large Language Model on Practice Questions for the Neonatal Board Examination

Published:2023-09-01 Issue:9 Volume:177 Page:977
ISSN:2168-6203
Container-title:JAMA Pediatrics
language:en
Short-container-title:JAMA Pediatr

Author:

Beam Kristyn¹,Sharma Puneet²,Kumar Bhawesh³,Wang Cindy⁴,Brodsky Dara¹,Martin Camilia R.⁵,Beam Andrew⁶

Affiliation:

1. Department of Neonatology, Beth Israel Deaconess Medical Center, Boston, Massachusetts

2. Division of Newborn Medicine, Boston Children’s Hospital, Boston, Massachusetts

3. Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, Massachusetts

4. Department of Statistics, Harvard University, Cambridge, Massachusetts

5. Division of Neonatology, Weill Cornell Medicine, New York, New York

6. Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts

Abstract

This Diagnostic/Prognostic Study evaluates the performance of a large language model in generating answers to practice questions for the neonatal-perinatal board examination.

Publisher

American Medical Association (AMA)

Subject

Pediatrics, Perinatology and Child Health

Link

https://jamanetwork.com/journals/jamapediatrics/articlepdf/2807329/jamapediatrics_beam_2023_ld_230028_1692993183.8971.pdf

Reference6 articles.

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3. Schulman? J, Zoph? B, Kim? C, . ChatGPT: optimizing language models for dialogue. OpenAI. Published November 30, 2022. Accessed February 28, 2023. https://chat.openai.com

4. Levine? DM, Tuwani? R, Kompa? B, . The diagnostic and triage accuracy of the gpt-3 artificial intelligence model.? medRxiv. Published online February 1, 2023. doi:10.1101/2023.01.30.23285067

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