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Overview Clear prompts help machine learning models become more accurate and reliable.Role-specific prompts generate focused ...
QNNs achieved 95 percent accuracy, while QSVMs reached 94 percent, both surpassing classical machine learning methods, which ...
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Machine learning to predict high-risk coronary artery disease on CT in the SCOT-HEART trial
Background Machine learning based on clinical characteristics has the potential to predict coronary CT angiography (CCTA) findings and help guide resource utilisation.Methods From the SCOT-HEART ...
Researchers at Tohoku University have applied explainable machine learning to identify key factors for nickel-based catalysts ...
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