首页|Capital Medical University Reports Findings in Endometrial Cancer (MRI-based rad iomics model for predicting endometrial cancer with high tumor mutation burden)
Capital Medical University Reports Findings in Endometrial Cancer (MRI-based rad iomics model for predicting endometrial cancer with high tumor mutation burden)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-New research on Oncology - Endometrial Cancer is the subject of a report. According to news reporting from Beijing, Pe ople's Republic of China, by NewsRx journalists, research stated, "To evaluate t he performance of MRI-based radiomics in predicting endometrial cancer (EC) with a high tumor mutation burden (TMB-H). A total of 122 patients with pathological ly confirmed EC (40 TMB-H, 82 non-TMB-H) were included in this retrospective stu dy." The news correspondents obtained a quote from the research from Capital Medical University, "Patients were randomly divided into training and testing cohorts in a ratio of 7:3. Radiomics features were extracted from sagittal T2-weighted ima ges and contrast-enhanced T1-weighted images. Then, the logistic regression (LR) , random forest (RF), and support vector machine (SVM) algorithms were used to c onstruct radiomics models. The area under the receiver operating characteristic curve (AUC) was calculated to evaluate the diagnostic performance of each model, and decision curve analysis was used to determine their clinical application va lue. Four radiomics features were selected to build the radiomics models. The th ree models had similar performance, achieving 0.771 (LR), 0.892 (RF), and 0.738 (SVM) in the training cohort, and 0.787 (LR), 0.798 (RF), and 0.777 (SVM) in the testing cohort. The decision curve demonstrated the good clinical application v alue of the LR model."
BeijingPeople's Republic of ChinaAsiaCancerEndometrial CancerGeneticsGynecologyHealth and MedicineMachin e LearningOncologySupport Vector MachinesWomen's Health
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