首页|Ohio State University Reports Findings in Machine Learning (Machine Learning Cla ssification of Integrin-Expression-Based Magnetic Sorted SW 620 Cells by Simulta neous O-PTIR and SERS)
Ohio State University Reports Findings in Machine Learning (Machine Learning Cla ssification of Integrin-Expression-Based Magnetic Sorted SW 620 Cells by Simulta neous O-PTIR and SERS)
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 Machine Learning is the subject of a report. According to news originating from Columbus, Ohio, by New sRx correspondents, research stated, “Immortalized cell lines are commonly used for in vitro studies such as drug efficacy, toxicology, and life cycle due to th eir cost effectiveness and accessibility; however, subpopulations within a cell line can arise from random mutations or asynchronous cell cycles which may lead to results that make interpretation difficult. A method that could classify these differences and separate unique subpopulations would increase our understandin g of heterogeneous cellular responses.”
ColumbusOhioUnited StatesNorth and Central AmericaCyborgsEmerging TechnologiesImmunologic ReceptorsIntegri nsMachine LearningMembrane Proteins
NETL
NSTL
