首页|Reports Outline Machine Learning Findings from Jackson Laboratory (A Machine Learning Approach for Quantifying Age-related Histological Changes In the Mouse Kidney)
Reports Outline Machine Learning Findings from Jackson Laboratory (A Machine Learning Approach for Quantifying Age-related Histological Changes In the Mouse Kidney)
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 DailyNews Daily News – Investigators publish new report on Machine Learning. According to news reportingoriginating from Bar Harbor, Maine, by NewsRx correspondents, research stated, “The ability to quantifyaging-related changes in histological samples is important, as it allows for evaluation of interventionsintended to effect health span. We used a machine learning architecture that can be trained to detect andquantify these changes in the mouse kidney.”Financial supporters for this research include NIH National Institute on Aging (NIA), National Institutesof Health (NIH) - USA.
Bar HarborMaineUnited StatesNorth and Central AmericaCyborgsEmerging TechnologiesMachine LearningJackson Laboratory
NETL
NSTL
