Chinese Academy of Sciences Reports Findings in Support Vector Machines (Radiomi c features add incremental benefit to conventional radiological feature-based di fferential diagnosis of lung nodules)
Chinese Academy of Sciences Reports Findings in Support Vector Machines (Radiomi c features add incremental benefit to conventional radiological feature-based di fferential diagnosis of lung nodules)
By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – New research on Machine Learning - Sup port Vector Machines is the subject of areport. According to news reporting ori ginating from Shenzhen, People’s Republic of China, by NewsRxcorrespondents, re search stated, “To investigate the incremental benefit of adding radiomic featur es toconventional semantic radiological feature-based differential diagnosis be tween benign and malignant lungnodules. From May 2017 to March 2021, 393 patien ts with 465 pathologically confirmed lung noduleswere enrolled with 54 patients with 54 lung nodules as external testing.”
Key words
Shenzhen/People’s Republic of China/As ia/Diagnostics and Screening/Health and Medicine/Machine Learning/Support Ve ctor Machines
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