首页|Beijing University of Technology Reports Findings in Machine Learning (Non-invasive fractional flow reserve derived from reduced-order coronary model and machine learning prediction of stenosis flow resistance)
Beijing University of Technology Reports Findings in Machine Learning (Non-invasive fractional flow reserve derived from reduced-order coronary model and machine learning prediction of stenosis flow resistance)
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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 Beijing, People’s Republic of China, by NewsRx correspondents, research stated, “Recently,computational fluid dynamics enables the non-invasive calculation of fractional flow reserve (FFR) basedon 3D coronary model, but it is time-consuming. Currently, machine learning technique has emerged asan efficient and reliable approach for prediction, which allows saving a lot of analysis time.”
BeijingPeople’s Republic of ChinaAsiaAngiologyCardiovascular Physiological PhenomenaCardiovascular Physiological ProcessesCyborgsEmerging TechnologiesHealth and MedicineHemodynamicsMachine LearningStenosis
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