首页|Southeast University Reports Findings in Support Vector Machines (Diffusion-/per fusion-weighted imaging fusion to automatically identify stroke within 4.5 h)
Southeast University Reports Findings in Support Vector Machines (Diffusion-/per fusion-weighted imaging fusion to automatically identify stroke within 4.5 h)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-New research on Machine Learning - Sup port Vector Machines is the subject of a report. According to news reporting out of Nanjing, People's Republic of China, by NewsRx editors, research stated, "We aimed to develop machine learning (ML) models based on diffusion- and perfusion -weighted imaging fusion (DP fusion) for identifying stroke within 4.5 h, to com pare them with DWIand/ or PWI-based ML models, and to construct an automatic se gmentation-classification model and compare with manual labeling methods. ML mod els were developed from multimodal MRI datasets of acute stroke patients within 24 h of clear symptom onset from two centers."
NanjingPeople's Republic of ChinaAsi aMachine LearningSupport Vector Machines
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