首页|Medical College of Wisconsin Reports Findings in Machine Learning (Comprehensive Clinical Usability-oriented Contour Quality Evaluation for Deep learning Auto-s egmentation: Combining Multiple Quantitative Metrics through Machine Learning)
Medical College of Wisconsin Reports Findings in Machine Learning (Comprehensive Clinical Usability-oriented Contour Quality Evaluation for Deep learning Auto-s egmentation: Combining Multiple Quantitative Metrics through Machine Learning)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – New research on Machine Learning is the subject of a report. According to news originating from Milwaukee, Wisconsin, by NewsRx correspondents, research stated, “The current commonlyused metrics fo r evaluating the quality of auto-segmented contours have limitations and do not always reflect the clinical usefulness of the contours. This work aims to develo p a novel contour quality classification (CQC) method by combining multiple quan titative metrics for clinical usability-oriented contour quality evaluation for deep learning-based auto-segmentation (DLAS).”
MilwaukeeWisconsinUnited StatesNor th and Central AmericaCyborgsEmerging TechnologiesMachine Learning
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