机器学习在放射治疗中的临床应用

放射治疗是癌症的主要治疗手段之一,以机器学习为代表的人工智能飞速发展,可应用于放射治疗临床实践的各个环节,包括临床决策支持、自动勾画靶区、预测疗效和副反应等,提高准确性与效率。尽管面临着结构化数据缺乏、模型可解释性差等挑战,机器学习在放射治疗中的应用将日趋深刻而广泛。本文从机器学习简介、在放射治疗中的临床应用研究进展和挑战与解决之道等3个方面展开综述。

Clinical application of machine learning in radiation oncology

Radiation therapy is one of the main treatment methods for cancer. Machine learning can be used in all aspects of clinical practice in radiation therapy, including clinical decision support, automatic segmentation of target volumes, prediction of treatment efficacy and side effects. Despite the challenges of lacking structured data and poor interpretability of models, the application of machine learning in radiotherapy will become increasingly profound and extensive. This review contains three aspects: introduction of machine learning, the clinical application of machine learning in radiotherapy, challenges and solutions.