医生不信任现有心电图自动分析，但期待未来更智能的AI辅助。
Contrasting Attitudes Towards Current and Future AI Applications for Computerised Interpretation of ECG: A Clinical Stakeholder Interview Study
- 通过访谈23名英国临床医生，研究对AI心电图解读的态度。
- 未来高精度AI即使不解释也能获得信任，视觉化结果更受欢迎。
- 关注AI带来的能力退化风险，强调需培训医生合理使用。
目的：探究临床医生对当前自动化心电图（ECG）解读及新型AI技术的态度，以及对计算机辅助解读的看法。方法：在英国对临床医生开展系列访谈，分析其对未来‘类人’计算方法在心电图解读与临床决策支持中的潜力，以及对算法可解释性与可信度的看法。结果：对23名医生的访谈转录文本进行归纳主题分析，识别出四大主题：（1）对现有系统缺乏信任；（2）对未来的AI应用持积极态度并提出要求；（3）算法准确率与可解释性之间的关系；（4）关于教育、可能的技能退化及AI对临床能力的影响。讨论：医生虽不信任现有自动化方法，但欢迎未来AI技术。当相信未来AI具备高准确性时，对其是否可解释的关注降低。医生更倾向于以可视化方式展示算法结果。尽管不担心失业，但担忧技能退化，强调需对医疗团队进行负责任使用AI的培训。结论：医生对AI在临床决策中的未来应用持积极态度。准确性是采纳的关键因素，视觉化呈现优于现有系统。这被视为潜在的培训与能力提升工具，而非仅带来技能退化。
原文摘要 · Abstract (English)
Objectives: To investigate clinicians' attitudes towards current automated interpretation of ECG and novel AI technologies and their perception of computer-assisted interpretation. Materials and Methods: We conducted a series of interviews with clinicians in the UK. Our study: (i) explores the potential for AI, specifically future 'human-like' computing approaches, to facilitate ECG interpretation and support clinical decision making, and (ii) elicits their opinions about the importance of explainability and trustworthiness of AI algorithms. Results: We performed inductive thematic analysis on interview transcriptions from 23 clinicians and identified the following themes: (i) a lack of trust in current systems, (ii) positive attitudes towards future AI applications and requirements for these, (iii) the relationship between the accuracy and explainability of algorithms, and (iv) opinions on education, possible deskilling, and the impact of AI on clinical competencies. Discussion: Clinicians do not trust current computerised methods, but welcome future 'AI' technologies. Where clinicians trust future AI interpretation to be accurate, they are less concerned that it is explainable. They also preferred ECG interpretation that demonstrated the results of the algorithm visually. Whilst clinicians do not fear job losses, they are concerned about deskilling and the need to educate the workforce to use AI responsibly. Conclusion: Clinicians are positive about the future application of AI in clinical decision-making. Accuracy is a key factor of uptake and visualisations are preferred over current computerised methods. This is viewed as a potential means of training and upskilling, in contrast to the deskilling that automation might be perceived to bring.
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