固定比率数据分割在放射学模型性能评估中的陷
1Department of Radiology, Children's Hospital of Chongqing Medical University, National Clinical Research Center for Child Health and Disorders, Ministry of Education Key Laboratory of Child Development and Disorders, Chongqing Key Laboratory of Child Neurodevelopment and Cognitive Disorders, Chongqing, China. wanghaoru615@126.com.
Abdominal radiology (New York)
|April 10, 2025
概括
放射学模型验证需要改进. 研究人员应该使用强大的交叉验证,而不是固定比率分割,以获得可靠的绩效评估.
科学领域:
- 医疗成像医学成像
- 放射学 放射学是一门学科.
- 数据科学数据科学数据科学
背景情况:
- 在过去的十年中,放射学已经显著增长,有大量的出版物.
- 放射学在医学诊断和预后方面提供了巨大的潜力.
- 目前的放射学研究在模型验证方面面临挑战.
研究的目的:
- 突出目前放射学模型验证方法的局限性.
- 倡导采用更强大的验证技术.
- 为了确保可靠和可重复的放射学模型性能.
主要方法:
- 分析放射学模型验证中的常见实践.
- 识别与单中心数据集和固定比率分割相关的问题.
- 对替代交叉验证策略的审查.
主要成果:
- 大多数放射学研究都使用单中心数据集.
- 固定比率的数据分割引入了变化,并降低了模型的可靠性.
- 数据分割中的随机性影响绩效评估.
结论:
- 固定比率的坚持方法对于强大的放射学模型验证是不够的.
- 实施严格的交叉验证技术至关重要.
- 采用先进的验证方法将提高放射学的临床实用性.
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