首页|Cancer Hospital Reports Findings in Disease Progression (Predicting Disease Prog ression in Inoperable Localized NSCLC Patients Using ctDNA Machine Learning Mode l)
Cancer Hospital Reports Findings in Disease Progression (Predicting Disease Prog ression in Inoperable Localized NSCLC Patients Using ctDNA Machine Learning Mode l)
扫码查看
点击上方二维码区域，可以放大扫码查看
原文链接
NETL
NSTL
By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – New research on Disease Attributes - D isease Progression is the subject of a report. According to news reporting out o f Beijing, People’s Republic of China, by NewsRx editors, research stated, “Ther e is an urgent clinical need to accurately predict the risk for disease progress ion in posttreatment NSCLC patients, yet current ctDNA mutation profiling appro aches are limited by low sensitivity. We represent a non-invasive liquid biopsy assay utilizing cfDNA neomer profiling for predicting disease progression in 44 inoperable localized NSCLC patients.”
BeijingPeople’s Republic of ChinaAsi aCyborgsDisease AttributesDisease ProgressionEmerging TechnologiesGene ticsHealth and MedicineMachine LearningRisk and Prevention
NETL
NSTL
