Studies from Henan University Yield New Data on Support Vector Machines (Low-dos e Ct Image Quality Evaluation Method Based On Radiomics and Deep Residual Networ k With Attention Mechanism)

Robotics & Machine Learning Daily News2024，Issue(Mar.19) ：17-18.DOI:10.1016/j.eswa.2023.122268

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Studies from Henan University Yield New Data on Support Vector Machines (Low-dos e Ct Image Quality Evaluation Method Based On Radiomics and Deep Residual Networ k With Attention Mechanism)

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Abstract

By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – A new study on Support Vector Machines is now available. According to news reporting from Kaifeng, People’s Republic o f China, by NewsRx journalists, research stated, “Low-dose computed tomography ( CT) produces less radiation but may degrade image quality. Research on automatic evaluation and classification of low-dose CT image quality is necessary, which is helpful to clinicians.”

Key words

Kaifeng/People’s Republic of China/Asi a/Emerging Technologies/Machine Learning/Support Vector Machines/Vector Mach ines/Henan University

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出版年

2024

Robotics & Machine Learning Daily News

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