Robotics & Machine Learning Daily News2024,Issue(Aug.26) :23-23.

Data on Machine Learning Reported by Zhubo Jiang and Colleagues (An Automated Ma chine Learning-Based Quantitative Multiparametric Approach for Mitral Regurgitat ion Severity Grading)

Robotics & Machine Learning Daily News2024,Issue(Aug.26) :23-23.

Data on Machine Learning Reported by Zhubo Jiang and Colleagues (An Automated Ma chine Learning-Based Quantitative Multiparametric Approach for Mitral Regurgitat ion Severity Grading)

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Abstract

By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – New research on Machine Learning is th e subject of a report. According to news reportingfrom Singapore, Singapore, by NewsRx journalists, research stated, “Considering the high prevalence ofmitral regurgitation (MR) and the highly subjective, variable MR severity reporting, a n automated tool thatcould screen patients for clinically significant MR ( mode rate) would streamline the diagnostic/therapeuticpathways and ultimately improv e patient outcomes. The authors aimed to develop and validate a fullyautomated machine learning (ML)-based echocardiography workflow for grading MR severity.”

Key words

Singapore/Singapore/Asia/Cardiology/Cardiovascular/Cyborgs/Diagnosis/Diagnostic Techniques and Procedures/Dopple r Echocardiography/Echocardiography/Emerging Technologies/Health and Medicine/Machine Learning

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出版年

2024
Robotics & Machine Learning Daily News

Robotics & Machine Learning Daily News

ISSN:
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