首页> 外文期刊>Robotics & Machine Learning Daily News >University of Waterloo Reports Findings in Deep Vein Thrombosis (Developing and optimizing a machine learning predictive model for post-thrombotic syndrome in a longitudinal cohort of patients with proximal deep venous thrombosis)
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University of Waterloo Reports Findings in Deep Vein Thrombosis (Developing and optimizing a machine learning predictive model for post-thrombotic syndrome in a longitudinal cohort of patients with proximal deep venous thrombosis)

机译:滑铁卢大学报告了深静脉血栓形成的发现(在近端深静脉血栓形成患者的纵向队列中开发和优化血栓形成后综合征的机器学习预测模型)

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By a News Reporter-Staff News Editor at Robotics Machine Learning DailyNews Daily News – New research on Cardiovascular Diseases and Conditions - Deep Vein Thrombosis is thesubject of a report. According to news reporting originating in Waterloo, Canada, by NewsRx journalists, research stated, “Post-thrombotic syndrome (PTS) is the most common chronic complication of deepvenous thrombosis (DVT). Risk measurement and stratification of PTS are crucial for DVT patients.”
机译:机器人技术与新闻记者新闻编辑机器学习日常心血管疾病和研究——深静脉血栓形成的条件的报告。加拿大滑铁卢原始NewsRx记者,研究指出,“Post-thrombotic综合征(PTS)是最常见的慢性病并发症的深风险测量和分层分深静脉血栓形成患者的关键。”

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