免疫疗法
医学
精密医学
个性化医疗
癌症
特征(语言学)
签名(拓扑)
人工智能
领域(数学)
机器学习
医学物理学
计算机科学
生物信息学
内科学
病理
几何学
数学
语言学
哲学
纯数学
生物
作者
Liusheng Wu,Xiaoqiang Li,Jun Yan
标识
DOI:10.1016/j.tranon.2024.101995
摘要
Machine learning has made great progress in the field of medicine, especially in oncology research showing significant potential. In this paper, the application of machine learning in the study of cholangiocarcinoma was discussed. By developing a novel intra-tumor heterogeneity feature, the study successfully achieved accurate prediction of prognosis and immunotherapy effect in patients with cholangiocarcinoma. This study not only provides strong support for personalized treatment, but also provides key information for clinicians to develop more effective treatment strategies. This breakthrough marks the continuous evolution of machine learning in cancer research and brings new hope for the future development of the medical field. Our study lays a solid foundation for deepening the understanding of the biological characteristics of cholangiocarcinoma and improving the therapeutic effect, and provides a useful reference for more extensive cancer research.
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