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Exploring the Potential of ChatGPT-4 in Responding to Common Questions About Abdominoplasty: An AI-Based Case Study
Wenbo Li1, Junjiang Chen2, Fengmin Chen3
1Department of Nursing, Jinzhou Medical University, Jinzhou, 121001, China.
Background:
With the increasing integration of artificial intelligence (AI) in health care, AI chatbots like ChatGPT-4 are being used to deliver health information.
Objectives:
This study aimed to assess the capability of ChatGPT-4 in answering common questions related to abdominoplasty, evaluating its potential as an adjunctive tool in patient education and preoperative consultation.
Methods:
A variety of common questions about abdominoplasty were submitted to ChatGPT-4. These questions were sourced from a question list provided by the American Society of Plastic Surgery to ensure their relevance and comprehensiveness. An experienced plastic surgeon meticulously evaluated the responses generated by ChatGPT-4 in terms of informational depth, response articulation, and competency to determine the proficiency of the AI in providing patient-centered information.
Results:
The study showed that ChatGPT-4 can give clear answers, making it useful for answering common queries. However, it struggled with personalized advice and sometimes provided incorrect or outdated references. Overall, ChatGPT-4 can effectively share abdominoplasty information, which may help patients better understand the procedure. Despite these positive findings, the AI needs more refinement, especially in providing personalized and accurate information, to fully meet patient education needs in plastic surgery.
Conclusions:
Although ChatGPT-4 shows promise as a resource for patient education, continuous improvements and rigorous checks are essential for its beneficial integration into healthcare settings. The study emphasizes the need for further research, particularly focused on improving the personalization and accuracy of AI responses.
Level Of Evidence V:
This journal requires that authors assign a level of evidence to each article. For a full description of these Evidence-Based Medicine ratings, please refer to the Table of Contents or the online Instructions to Authors www.springer.com/00266 .
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