Wang Haoru
Department 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.
Abdom Radiol (NY). 2025 Apr 10. doi: 10.1007/s00261-025-04936-6.
Over the past decade, radiomics has seen exponential growth, with over ten thousand publications in PubMed and a steady increase in related studies in journals like Abdominal Radiology. Despite the potential of radiomics, a major challenge lies in validating radiomics models, as most studies rely on single-center datasets with fixed-ratio splits, which can lead to variability in performance due to randomness in data splitting. Therefore, researchers should adopt more robust cross-validation methods rather than relying solely on the fixed-ratio holdout method to ensure robust and reliable radiomics model performance evaluation.
在过去十年中，放射组学呈指数级增长，在PubMed上有一万多篇相关出版物，并且在《腹部放射学》等期刊上的相关研究也在稳步增加。尽管放射组学具有潜力，但一个主要挑战在于验证放射组学模型，因为大多数研究依赖于具有固定比例划分的单中心数据集，这可能由于数据划分的随机性而导致性能的变异性。因此，研究人员应采用更稳健的交叉验证方法，而不是仅仅依赖于固定比例的留出法，以确保对放射组学模型性能进行稳健且可靠的评估。
