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Southeast University Reports Findings in Machine Learning (Optical coherence tomography for identification of malignant pulmonary nodules based on random forest machine learning algorithm)

机译:东南大学报告机器学习研究成果(基于随机森林机器学习算法的光学相干断层扫描识别恶性肺结节)

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By a News Reporter-Staff News Editor at Robotics Machine Learning DailyNews – New research on Machine Learning is the subject of a report. According to news reporting fromJiangsu, People’s Republic of China, by NewsRx journalists, research stated, “To explore the feasibilityof using random forest (RF) machine learning algorithm in assessing normal and malignant peripheralpulmonary nodules based on in vivo endobronchial optical coherence tomography (EB-OCT). A total of 31patients with pulmonary nodules were admitted to Department of Respiratory Medicine, Zhongda Hospital,Southeast University, and underwent chest CT, EB-OCT and biopsy.”
机译:《机器人与机器学习每日新闻》(Robotics & Machine Learning Daily News)的新闻记者-新闻编辑 - 关于机器学习的新研究是报告的主题。根据NewsRx记者从中华人民共和国江苏报道,研究表明,“探索使用随机森林(RF)机器学习算法评估基于体内支气管内光学相干断层扫描(EB-OCT)的正常和恶性外周肺结节的可行性。共收治31例肺结节患者入住东南大学中大医院呼吸内科,行胸部CT、EB-OCT和活检。

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