人工智能在甲状腺眼病评估中的应用 (TED) - - 范围审查
Chiaw-Ling Chng1, Kaiping Zheng2, Ann Kerwen Kwee1
1Department of Endocrinology, Singapore General Hospital, Singapore, Singapore.
Frontiers in endocrinology
|January 4, 2024
概括
人工智能 (AI) 在甲状腺眼病 (TED) 评估中显示出高诊断准确度. 然而,研究设计缺陷影响了可靠性,需要为TED的未来机器学习研究提供标准化的指导.
科学领域:
- 眼科医生 眼科 眼科
- 医疗成像医学成像
- 人工智能的人工智能
背景情况:
- 新出现的证据支持人工智能 (AI) 用于诊断和评估甲状腺眼病 (TED).
- 在TED评估中的人工智能应用正在迅速发展.
- 这篇评论侧重于TED中人工智能的当前证据基础.
研究的目的:
- 在TED中确定可用的AI研究的范围.
- 在TED研究中分析人工智能研究的方法.
- 为TED确定人工智能研究中的知识差距.
主要方法:
- 根据PRISMA指南进行范围审查.
- 人工智能模型的量化诊断准确性用于TED.
- 使用修改后的 QUADAS-2 工具评估研究质量.
主要成果:
- 包括13项研究,主要使用卷积神经网络 (CNN).
- 大多数研究表明,人工智能在识别TED特征时具有很高的诊断准确性.
- 确定了研究设计的重大缺陷,特别是研究流程和时间,导致偏见和适用性问题.
结论:
- 人工智能模型在TED评估中表现出高的诊断准确性.
- 研究设计的局限性和偏见损害了TED当前人工智能研究的适用性.
- 对研究设计,报告和立法框架的标准化指导对于推进TED研究中的AI至关重要.
相关概念视频
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