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The evaluation of the performance of ChatGPT in the management of labor analgesia.
Ismaiel, Nada; Nguyen, Teresa Phuongtram; Guo, Nan; Carvalho, Brendan; Sultan, Pervez.
Afiliação
  • Ismaiel N; Department of Anesthesiology, El Camino Health, 2500 Grant Road, Mountain View, California 94040, USA.
  • Nguyen TP; Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University School of Medicine, 300 Pasteur Drive, Room H3580, MC 5640, Stanford 94305, CA, USA. Electronic address: Teresa.pt.nguyen@stanford.edu.
  • Guo N; Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University School of Medicine, 300 Pasteur Drive, Room H3580, MC 5640, Stanford 94305, CA, USA. Electronic address: nguo3@stanford.edu.
  • Carvalho B; Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University School of Medicine, 300 Pasteur Drive, Room H3580, MC 5640, Stanford 94305, CA, USA. Electronic address: carvalb@stanford.edu.
  • Sultan P; Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University School of Medicine, 300 Pasteur Drive, Room H3580, MC 5640, Stanford 94305, CA, USA. Electronic address: psultan@stanford.edu.
J Clin Anesth ; 98: 111582, 2024 Nov.
Article em En | MEDLINE | ID: mdl-39167880
ABSTRACT
ChatGPT4 is a leading large language model (LLM) chatbot released by OpenAI in 2023. ChatGPT4 can respond to free-text queries, answer questions and make suggestions regarding virtually any topic. ChatGPT4 has successfully answered anesthesia and even obstetric anesthesia knowledge-based questions with reasonable accuracy. However, ChatGPT4 has yet to be challenged in obstetric anesthesia clinical decision-making. STUDY

OBJECTIVE:

In this study, we evaluated the performance of ChatGPT4 in the management of clinical labor analgesia scenarios compared to expert obstetric anesthesiologists. INTERVENTION Eight clinical questions with progressively increasing medical complexity were posed to ChatGPT4. MEASUREMENTS The ChatGPT4 responses were rated by seven expert obstetric anesthesiologists based on safety, accuracy and completeness of each response using a five-point Likert rating scale. MAIN

RESULTS:

ChatGPT4 was deemed safe in 73% of responses to the presented obstetric anesthesia clinical scenarios (27% of responses were deemed unsafe). None of the ChatGPT4 responses were unanimously deemed to be safe by all seven expert obstetric anesthesiologists. Moreover, ChatGPT4 responses were overall partly accurate (score 4 out of 5) and somewhat incomplete (score 3.5 out of 5).

CONCLUSIONS:

In summary, approximately one quarter of all responses by ChatGPT4 were deemed unsafe by expert obstetric anesthesiologists. These findings may suggest the need for more fine-tuning and training of LLMs such as ChatGPT4 specifically for clinical decision making in obstetric anesthesia or other specialized medical fields. These LLMs may come to play an important future role in assisting obstetric anesthesiologists in clinical decision making and enhancing overall patient care.
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Analgesia Obstétrica / Dor do Parto / Manejo da Dor / Aprendizado de Máquina Idioma: En Ano de publicação: 2024 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Analgesia Obstétrica / Dor do Parto / Manejo da Dor / Aprendizado de Máquina Idioma: En Ano de publicação: 2024 Tipo de documento: Article