首页|Shanghai Jiao Tong University Reports Findings in Ovarian Cancer (Comprehensive machine learning-based preoperative blood features predict the prognosis for ova rian cancer)
Shanghai Jiao Tong University Reports Findings in Ovarian Cancer (Comprehensive machine learning-based preoperative blood features predict the prognosis for ova rian cancer)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-New research on Oncology - Ovarian Can cer is the subject of a report.According to news reporting originating in Shang hai,People's Republic of China,by NewsRx journalists,research stated,"Signif icant advancements in improving ovarian cancer (OC) outcomes have been limited o ver the past decade.To predict prognosis and improve outcomes of OC,we plan to develop and validate a robust prognosis signature based on blood features." Financial support for this research came from National Natural Science Foundatio n of China.The news reporters obtained a quote from the research from Shanghai Jiao Tong Un iversity,"We screened age and 33 blood features from 331 OC patients.Using ten machine learning algorithms,88 combinations were generated,from which one was selected to construct a blood risk score (BRS) according to the highest C-index in the test dataset.Stepcox (both) and Enet (alpha = 0.7) performed the best in the test dataset with a C-index of 0.711.Meanwhile,the low RBS group possess ed observably prolonged survival in this model.Compared to traditional prognost ic-related features such as age,stage,grade,and CA125,our combined model had the highest AUC values at 3,5,and 7 years.According to the results of the mo del,BRS can provide accurate predictions of OC prognosis.BRS was also capable of identifying various prognostic stratifications in different stages and grades .Importantly,developing the nomogram may improve performance by combining BRS and stage."
ShanghaiPeople's Republic of ChinaAs iaCancerCyborgsEmerging TechnologiesGynecologyHealth and MedicineMac hine LearningOncologyOvarian CancerWomen's Health
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