<p class="jove_content">This study compared five machine learning algorithms for thyroid nodule classification using super-resolution ultrasound features. SVM performed best (accuracy 68.6%, Area Under the Curve 0.690), identifying microcalcification and post-contrast enlargement as key contributors, but the findings require external validation before clinical use.</p>

quantitative-super-resolution-ultrasound-microvascular-features-for

Quantitative Super-Resolution Ultrasound Microvascular Features for Machine Learning-Based Classification of Thyroid Nodules

This study compared five machine learning algorithms&#8212;Random Forest (RF), Support Vector Machine (SVM), Decision Tree (DT), eXtreme Gradient Boosting ...

Institution - Zhenjiang Hospital of Chinese Traditional and Western Medicine

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