无线电技术
放射性肺炎
荟萃分析
系统回顾
医学物理学
医学
计算机科学
计量经济学
放射治疗
人工智能
梅德林
数学
放射科
内科学
政治学
法学
作者
Heesoon Sheen,Wonyoung Cho,Changhwan Kim,Min Cheol Han,Hojin Kim,Ho Lee,Dong‐Wook Kim,Jin Sung Kim,Chae‐Seon Hong
出处
期刊:Physica Medica
[Elsevier]
日期:2024-06-20
卷期号:123: 103414-103414
被引量:1
标识
DOI:10.1016/j.ejmp.2024.103414
摘要
This study reviewed and meta-analyzed evidence on radiomics-based hybrid models for predicting radiation pneumonitis (RP). These models are crucial for improving thoracic radiotherapy plans and mitigating RP, a common complication of thoracic radiotherapy. We examined and compared the RP prediction models developed in these studies with the radiomics features employed in RP models.
科研通智能强力驱动
Strongly Powered by AbleSci AI