人工智能算法的诊断准确性与放射科医生对宫脊椎CTCT骨折检测的诊断准确性
Gaby J van den Wittenboer1,2, Brigitta Y M van der Kolk3,4,5, Ingrid M Nijholt3
1Department of Radiology and Nuclear Medicine, Isala, Dr. van Heesweg 2, Zwolle, The Netherlands. g.j.wittenboer@isala.nl.
European radiology
|January 11, 2024
概括
人工智能 (AI) 显示出在CT扫描上检测椎骨折的潜力,但其灵敏度低于放射科医生. 人工智能识别了放射科医生错过的大部分骨折,包括需要稳定治疗的严重损伤.
科学领域:
- 放射学 放射学是一门学科.
- 人工智能的人工智能
- 医疗成像医学成像
背景情况:
- 椎骨折需要准确和及时的诊断.
- 深度学习人工智能 (AI) 提供了改善医学成像诊断准确性的潜力.
研究的目的:
- 为了比较人工智能算法在CT扫描上检测C脊柱骨折的诊断准确度,与参与放射科医生进行比较.
- 评估AI识别需要立即稳定治疗 (IST) 的骨折的能力.
主要方法:
- 一项回顾性研究分析了来自18岁及以上患者的2368张CT扫描.
- 骨折的基本真相是由放射科医生和神经外科医生对扫描的独立审查确立的.
- 人工智能和放射科医生的诊断准确性使用麦克纳马的测试进行了比较.
主要成果:
- 人工智能检测到71.5%的C-脊柱骨折,而放射科医生检测到88.2% (p < 0.001).
- 与放射科医生相比,AI在需要IST的骨折中失误率更高 (30/63) (4/26).
- 人工智能成功识别了84.6%的骨折被放射科医生错过,包括4个IST中的3个.
结论:
- 人工智能算法对C-脊柱骨折检测的灵敏度低于参加放射科医生的灵敏度.
- 尽管灵敏度较低,但人工智能识别了放射科医生错过的骨折的很大一部分,包括需要稳定治疗的骨折.
- 人工智能显示出作为放射科医生在C-脊柱骨折检测中的辅助工具的承诺.
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