{"title":"人工智能在放射治疗剂量预测中的应用和进展","authors":"Chen Jiang, Tianlong Ji, Qiao Qiao","doi":"10.1016/j.ctro.2024.100792","DOIUrl":null,"url":null,"abstract":"<div><p>Radiation therapy (RT) nowadays is a main treatment modality of cancer. To ensure the therapeutic efficacy of patients, accurate dose distribution is often required, which is a time-consuming and labor-intensive process. In addition, due to the differences in knowledge and experience among participants and diverse institutions, the predicted dose are often inconsistent. In last several decades, artificial intelligence (AI) has been applied in various aspects of RT, several products have been implemented in clinical practice and confirmed superiority. In this paper, we will review the research of AI in dose prediction, focusing on the progress in deep learning (DL).</p></div>","PeriodicalId":10342,"journal":{"name":"Clinical and Translational Radiation Oncology","volume":"47 ","pages":"Article 100792"},"PeriodicalIF":2.7000,"publicationDate":"2024-05-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2405630824000697/pdfft?md5=19485973fd871948e35b3d07858d4375&pid=1-s2.0-S2405630824000697-main.pdf","citationCount":"0","resultStr":"{\"title\":\"Application and progress of artificial intelligence in radiation therapy dose prediction\",\"authors\":\"Chen Jiang, Tianlong Ji, Qiao Qiao\",\"doi\":\"10.1016/j.ctro.2024.100792\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>Radiation therapy (RT) nowadays is a main treatment modality of cancer. To ensure the therapeutic efficacy of patients, accurate dose distribution is often required, which is a time-consuming and labor-intensive process. In addition, due to the differences in knowledge and experience among participants and diverse institutions, the predicted dose are often inconsistent. In last several decades, artificial intelligence (AI) has been applied in various aspects of RT, several products have been implemented in clinical practice and confirmed superiority. In this paper, we will review the research of AI in dose prediction, focusing on the progress in deep learning (DL).</p></div>\",\"PeriodicalId\":10342,\"journal\":{\"name\":\"Clinical and Translational Radiation Oncology\",\"volume\":\"47 \",\"pages\":\"Article 100792\"},\"PeriodicalIF\":2.7000,\"publicationDate\":\"2024-05-09\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.sciencedirect.com/science/article/pii/S2405630824000697/pdfft?md5=19485973fd871948e35b3d07858d4375&pid=1-s2.0-S2405630824000697-main.pdf\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Clinical and Translational Radiation Oncology\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2405630824000697\",\"RegionNum\":3,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"ONCOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Clinical and Translational Radiation Oncology","FirstCategoryId":"3","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2405630824000697","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ONCOLOGY","Score":null,"Total":0}
Application and progress of artificial intelligence in radiation therapy dose prediction
Radiation therapy (RT) nowadays is a main treatment modality of cancer. To ensure the therapeutic efficacy of patients, accurate dose distribution is often required, which is a time-consuming and labor-intensive process. In addition, due to the differences in knowledge and experience among participants and diverse institutions, the predicted dose are often inconsistent. In last several decades, artificial intelligence (AI) has been applied in various aspects of RT, several products have been implemented in clinical practice and confirmed superiority. In this paper, we will review the research of AI in dose prediction, focusing on the progress in deep learning (DL).