糖尿病和代谢性疾病领域应用 ChatGPT 的效益-风险评估:定性研究。

IF 2.7 Q3 ENDOCRINOLOGY & METABOLISM
Ammar Abdulrahman Jairoun, Sabaa Saleh Al-Hemyari, Moyad Shahwan, Tariq Al-Qirim, Monzer Shahwan
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引用次数: 0

摘要

背景:在代谢和内分泌疾病的管理中使用 ChatGPT 和人工智能(AI)既是重大机遇,也存在明显风险:通过探讨内分泌专家和糖尿病专家的观点,研究在糖尿病和代谢疾病管理中应用 ChatGPT 所带来的益处和风险:本研究采用了定性研究方法。制定了半结构化深度访谈指南。对 25 名内分泌科医生和糖尿病医生进行了抽样和访谈。所有访谈都进行了录音和逐字记录,然后采用主题分析法确定数据中的主题:专题分析的结果产生了 19 个代码和 9 个主要专题,涉及实施人工智能和 ChatGPT 在管理糖尿病和代谢性疾病方面的益处。此外,提取的在糖尿病和代谢性疾病管理中实施人工智能和 ChatGPT 的风险分为 7 个主题和 14 个代码。提高诊断精确度、量身定制治疗和有效利用资源的优势有可能改善患者的治疗效果。同时,对潜在挑战的识别,如数据安全问题和对可解释的人工智能的需求,使利益相关者能够积极主动地解决这些问题:监管框架必须与时俱进,以跟上人工智能在医疗保健领域的快速应用。持续关注伦理方面的考虑,包括征得患者同意、保护数据隐私、确保问责制和促进公平,仍然至关重要。尽管人工智能对医疗保健的人性化方面有潜在影响,但它仍将是以患者为中心的医疗保健不可或缺的组成部分。在人工智能辅助决策和人类专业知识之间取得平衡对于维护信任和提供全面的患者护理至关重要。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Benefit-Risk Assessment of ChatGPT Applications in the Field of Diabetes and Metabolic Illnesses: A Qualitative Study.

Background: The use of ChatGPT and artificial intelligence (AI) in the management of metabolic and endocrine disorders presents both significant opportunities and notable risks.

Objectives: To investigate the benefits and risks associated with the application of ChatGPT in managing diabetes and metabolic illnesses by exploring the perspectives of endocrinologists and diabetologists.

Methods and materials: The study employed a qualitative research approach. A semi-structured in-depth interview guide was developed. A convenience sample of 25 endocrinologists and diabetologists was enrolled and interviewed. All interviews were audiotaped and verbatim transcribed; then, thematic analysis was used to determine the themes in the data.

Results: The findings of the thematic analysis resulted in 19 codes and 9 major themes regarding the benefits of implementing AI and ChatGPT in managing diabetes and metabolic illnesses. Moreover, the extracted risks of implementing AI and ChatGPT in managing diabetes and metabolic illnesses were categorized into 7 themes and 14 codes. The benefits of heightened diagnostic precision, tailored treatment, and efficient resource utilization have potential to improve patient results. Concurrently, the identification of potential challenges, such as data security concerns and the need for AI that can be explained, enables stakeholders to proactively tackle these issues.

Conclusions: Regulatory frameworks must evolve to keep pace with the rapid adoption of AI in healthcare. Sustained attention to ethical considerations, including obtaining patient consent, safeguarding data privacy, ensuring accountability, and promoting fairness, remains critical. Despite its potential impact on the human aspect of healthcare, AI will remain an integral component of patient-centered care. Striking a balance between AI-assisted decision-making and human expertise is essential to uphold trust and provide comprehensive patient care.

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来源期刊
CiteScore
4.30
自引率
0.00%
发文量
15
审稿时长
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