The use of artificial intelligence in anesthesiology: Attitudes and ethical concerns of anesthesiologists

人工智能在麻醉学中的应用:麻醉医师的态度和伦理考量

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Abstract

BACKGROUND: Existing studies on anesthesiologists' attitudes toward artificial intelligence (AI) leave a global understanding underexplored. This cross-sectional study aims to investigate Turkish anesthesiologists' attitudes toward AI, examining its perceived benefits, limitations, and associated ethical concerns. Insights from this study aim to enhance understanding of AI's role in anesthesiology within a cultural and ethical context. METHODS: This nationwide study surveyed Turkish anesthesiologists. Descriptive statistics summarized categorical variables, Pearson's Chi-square test compared variables between groups. Binary logistic regression analyzed associations between demographic factors and positive attitudes toward AI. RESULTS: Among 293 valid responses, 69.6% of participants expressed positive attitudes toward AI. Gender (P = 0.01), employment setting (P < 0.001), and prior AI experience (P < 0.001) were significant predictors of positive attitudes. AI applications most frequently endorsed included preoperative assessments (93.1%), academic support (95.2%), and medical education (91.2%). Ethical concerns were prominent, with liability ambiguity (87.3%) and privacy issues (62.8%) being the most cited. Logistic regression revealed that participants aged 46-55 were significantly more likely to exhibit positive attitudes (OR = 3.744, P = 0.03), while those with over 15 years of experience were less likely to do so (OR = 0.105, P = 0.04). CONCLUSIONS: Turkish anesthesiologists exhibited predominantly positive attitudes toward AI, with prior experience playing a significant role in shaping perceptions. While AI was embraced for academic, educational, and noninvasive tasks, skepticism was present toward its application in invasive procedures. These findings highlight AI's potential to enhance efficiency and patient safety while underscoring the need for comprehensive legal and ethical frameworks.

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