Artificial intelligence: Reducing inconsistency in the surgical residency application review process.

Journal

American journal of surgery
ISSN: 1879-1883
Titre abrégé: Am J Surg
Pays: United States
ID NLM: 0370473

Informations de publication

Date de publication:
07 Jul 2024
Historique:
received: 19 04 2024
revised: 12 06 2024
accepted: 01 07 2024
medline: 31 7 2024
pubmed: 31 7 2024
entrez: 30 7 2024
Statut: aheadofprint

Résumé

The incorporation of artificial intelligence (AI) into the general surgery residency recruitment process holds great promise for overcoming limitations inherent to traditional application review methods. This study assesses the consistency of AI, particularly ChatGPT, in evaluating medical student performance evaluation (MSPE) letters in comparison to experienced human reviewers. While the results suggest that ChatGPT demonstrates greater consistency in grading than human reviewers, AI still has its limitations. This underscores the necessity for careful refinement and consideration in its implementation. While AI presents opportunities to enhance residency selection procedures, further research is imperative to fully grasp its capabilities and implications.

Identifiants

DOI: 10.1016/j.amjsurg.2024.115816 PMID: 39079879
pubmed: 39079879
pii: S0002-9610(24)00368-4
doi: 10.1016/j.amjsurg.2024.115816
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

115816

Informations de copyright

Copyright © 2024 Elsevier Inc. All rights reserved.

Déclaration de conflit d'intérêts

Declaration of competing interest We have no conflicts of interest to disclose.

Auteurs

Megan Markow (M)

University of California, Irvine, Department of Surgery, Division of Trauma, Burns and Surgical Critical Care, Orange, CA, USA.

Mallory Jebbia (M)

University of California, Irvine, Department of Surgery, Division of Trauma, Burns and Surgical Critical Care, Orange, CA, USA.

Bima J Hasjim (BJ)

University of California, Irvine, Department of Surgery, Division of Trauma, Burns and Surgical Critical Care, Orange, CA, USA.

Jeffry Nahmias (J)

University of California, Irvine, Department of Surgery, Division of Trauma, Burns and Surgical Critical Care, Orange, CA, USA.

Areg Grigorian (A)

University of California, Irvine, Department of Surgery, Division of Trauma, Burns and Surgical Critical Care, Orange, CA, USA.

Sigrid Burruss (S)

University of California, Irvine, Department of Surgery, Division of Trauma, Burns and Surgical Critical Care, Orange, CA, USA.

Sebastian Schubl (S)

University of California, Irvine, Department of Surgery, Division of Trauma, Burns and Surgical Critical Care, Orange, CA, USA.

Valery Vilchez (V)

University of California, Irvine, Department of Surgery, Division of Trauma, Burns and Surgical Critical Care, Orange, CA, USA.

Kelly Fairbairn (K)

University of California, Irvine, Department of Surgery, Division of Trauma, Burns and Surgical Critical Care, Orange, CA, USA.

Anthony Chau (A)

University of California, Irvine, Department of Surgery, Division of Trauma, Burns and Surgical Critical Care, Orange, CA, USA.

Hari Keshava (H)

University of California, Irvine, Department of Surgery, Division of Trauma, Burns and Surgical Critical Care, Orange, CA, USA.

Maki Yamamoto (M)

University of California, Irvine, Department of Surgery, Division of Trauma, Burns and Surgical Critical Care, Orange, CA, USA.

Brian Smith (B)

University of California, Irvine, Department of Surgery, Division of Trauma, Burns and Surgical Critical Care, Orange, CA, USA.

Lourdes Swentek (L)

University of California, Irvine, Department of Surgery, Division of Trauma, Burns and Surgical Critical Care, Orange, CA, USA. Electronic address: lyrobles@hs.uci.edu.

Classifications MeSH