放射组学是人工智能的一个新兴领域，专注于从医学图像中提取和分析强度、形状、纹理和空间关系等定量特征。这些特征通常是人眼无法察觉的，但却可以揭示复杂的模式和生物学见解。它们还可以与临床数据相结合，利用机器学习创建预测模型，以改善核医学中的疾病特征。这篇综述文章探讨了核医学中放射组学的现状，并展示了其改善患者护理的潜力。研究了癌症、神经退行性疾病、心血管问题和甲状腺疾病等疾病的选定临床应用。文章最后对将研究结果与临床实践联系起来的未来前景和策略进行了简要分类。Thieme。版权所有。

Radiomics is an emerging field of artificial intelligence that focuses on the extraction and analysis of quantitative features such as intensity, shape, texture and spatial relationships from medical images. These features, often imperceptible to the human eye, can reveal complex patterns and biological insights. They can also be combined with clinical data to create predictive models using machine learning to improve disease characterization in nuclear medicine. This review article examines the current state of radiomics in nuclear medicine and shows its potential to improve patient care. Selected clinical applications for diseases such as cancer, neurodegenerative diseases, cardiovascular problems and thyroid diseases are examined. The article concludes with a brief classification in terms of future perspectives and strategies for linking research findings to clinical practice.Thieme. All rights reserved.