効果的な術前計画のための大規模言語モデルの活用:麻酔管理の最適化
Mary Scott-Herring1, Katherine Thorpe, Nancy Crowell
1Doctor of Nurse Anesthesia Practice (DNAP) Program (Drs Scott-Herring, Thorpe, and McAuliffe) and School of Nursing (Dr Crowell), Georgetown University, Washington, DC.
Abstract:
Although artificial intelligence has quickly gained widespread popularity, there is a gap in the research regarding the usefulness of using large language models in the context of clinical practice. The purpose of this study was to examine the effectiveness of utilizing ChatGPT for the creation of anesthesia care plans. First-year nurse anesthesiology resident participants were instructed to enter perceived key anesthesia care plan variables into ChatGPT. The input provided to ChatGPT by the resident and the ChatGPT-generated output was collected and reviewed independently by three assistant professors of a doctor of nurse anesthesia practice program. It was determined that ChatGPT formed an appropriate anesthetic plan based on medical history and home medications. However, ChatGPT did not adequately address key variables such as ventilator settings, fluid plans, or medication doses . Artificial intelligence programs such as ChatGPT can be useful tools in the creation of anesthesia care plans; however, its effectiveness is reliant on clear input from an educated user.
関連する概念動画
General Anesthesia: Overview
General anesthesia induces unconsciousness in the whole body, while the others target specific areas or sensations. It is administered to minimize adverse effects, maintain...
Stages of General Anesthesia
Parenteral Anesthetics: Overview
Inhalational Anesthetics: Overview
Cardiomyopathy VII: Pre and Post Operative Nursing Management
Local Anesthetics: Clinical Application as Spinal Anesthesia


