首页|Data on Machine Learning Reported by Bruna Punzo and Colleagues (Unsupervised machine learning for risk stratification and identification of relevant subgroups of ascending aorta dimensions using cardiac CT and clinical data)
Data on Machine Learning Reported by Bruna Punzo and Colleagues (Unsupervised machine learning for risk stratification and identification of relevant subgroups of ascending aorta dimensions using cardiac CT and clinical data)
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 – New research on Machine Learning is the subject of a report. According to newsoriginating from Naples, Italy, by NewsRx correspondents, research stated, “The potential of precisionpopulation health lies in its capacity to utilize robust patient data for customized prevention and caretargeted at specific groups. Machine learning has the potential to automatically identify clinically relevantsubgroups of individuals, considering heterogeneous data sources.”
NaplesItalyEuropeAngiologyAortaBusinessCardiologyCyborgsEmerging TechnologiesHealth and MedicineMachine Learning
NETL
NSTL
