| Literature DB >> 36016617 |
Yun Qin1, Li-Hua Zhu1, Wei Zhao1, Jun-Jie Wang2, Hao Wang2,3.
Abstract
By breaking the traditional medical image analysis framework, precision medicine-radiomics has attracted much attention in the past decade. The use of various mathematical algorithms offers radiomics the ability to extract vast amounts of detailed features from medical images for quantitative analysis and analyzes the confidential information related to the tumor in the image, which can establish valuable disease diagnosis and prognosis models to support personalized clinical decisions. This article summarizes the application of radiomics and dosiomics in radiation oncology. We focus on the application of radiomics in locally advanced rectal cancer and also summarize the latest research progress of dosiomics in radiation tumors to provide ideas for the treatment of future related diseases, especially 125I CT-guided radioactive seed implant brachytherapy.Entities:
Keywords: deep learning; dosiomics; machine learning; radiomics; rectal cancer
Year: 2022 PMID: 36016617 PMCID: PMC9395725 DOI: 10.3389/fonc.2022.913683
Source DB: PubMed Journal: Front Oncol ISSN: 2234-943X Impact factor: 5.738