人工智能在肝病学中的应用障碍以及如何克服这些障碍
Jan Clusmann1, Maria Balaguer-Montero2, Octavi Bassegoda3
1Else Kroener Fresenius Center for Digital Health, Technical University Dresden, Dresden, Germany; Department of Medicine III, University Hospital RWTH Aachen, Aachen, Germany.
肝病学中的人工智能 (AI) 是有前途的,但由于整合挑战,其采用程度有限. 关键建议侧重于临床试验中的AI,系统集成和临床医生的AI素养,以推动采用.
科学领域:
- 肝病学 肝病学是一种肝病学.
- 医疗信息学 医疗信息学
- 人工智能的人工智能
背景情况:
- 自2010年代中期以来,人工智能 (AI) 方法在肝病学中迅速发展,出版物增加和一些监管批准.
- 尽管分析复杂数据 (组织病理学,放射学,多组学,患者数据) 有明显的好处,但AI在临床实践和研究中的应用仍然有限.
- 实质性障碍阻碍了人工智能的整合到肝病学中的常规临床工作流程中.
研究的目的:
- 评估阻碍人工智能在肝病学领域采用的局限性.
- 为AI系统开发和肝脏病学环境提出明确的建议,以促进临床整合.
- 推动基于人工智能的诊断,预后和预测工具向临床护理过渡.
主要方法:
- 一份评估当前局限性的立场文件,并提出建议.
- 通过德尔菲共识验证,涉及34名肝病学,人工智能和数据科学国际专家.
- 专注于专家的共识,以确保对建议的全面评估.
主要成果:
- 确定了人工智能在临床肝病学实践中整合的主要障碍.
- 针对人工智能开发和临床环境的建议建议.
- 专家共识验证了提议的增强人工智能采用策略.
结论:
- 在肝病学中采用人工智能需要解决整合障碍.
- 战略建议包括在临床试验中利用AI,无整合医院信息系统,提高临床医生的AI素养.
- 这些策略对于人工智能工具成功转化为常规肝病治疗至关重要.
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