Radiomics in preclinical imaging research: methods, challenges and opportunities
7.0
来源：
Nature
关键字：
medical imaging+deep learning
发布时间：
2025-09-22 19:32
摘要：
Radiomics is a rapidly evolving field in preclinical imaging, offering methods to extract complex data from medical images. This review discusses its applications in disease characterization, treatment response assessment, and drug development. The challenges of high dimensionality and limited sample sizes in preclinical studies are addressed, alongside the potential for integrating radiomics with machine learning to enhance predictive modeling. The findings suggest that radiomics can significantly contribute to understanding diseases and improving therapeutic strategies.
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1.5
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关键证据
Radiomics-based analyses are increasingly being applied to clinical studies.
Preclinical studies allow for in-depth histologic investigations.
Radiomics could also be applied to preclinical studies to test novel therapies or drugs.
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AI评分总结
Radiomics is a rapidly evolving field in preclinical imaging, offering methods to extract complex data from medical images. This review discusses its applications in disease characterization, treatment response assessment, and drug development. The challenges of high dimensionality and limited sample sizes in preclinical studies are addressed, alongside the potential for integrating radiomics with machine learning to enhance predictive modeling. The findings suggest that radiomics can significantly contribute to understanding diseases and improving therapeutic strategies.