Machine Learning Algorithms Outperform Inexperienced Radiologists

Linked Articles Machine learning algorithms may help less experienced radiologists differentiate malignant and benign thyroid nodules through ultrasound, according to a study published in the American Journal of Roentgenology. Researchers from China sought to construct classifier models using machine learning algorithms and to evaluate their diagnostic performance for differentiating malignant from benign thyroid nodules. Two radiologists respectively reviewed ultrasound images of 970 histopathologically proven thyroid nodules in 970 patients and their findings were compared with machine-building algorithms: the Naïve Bayes classifier, the support vector machine, and the radial basis neural function network. The nodules were graded according to a five-tier sonographic scoring system. The performance of the machine learning algorithms and radiologists were compared using ROC curve analysis. A total of 507 nodules (52.3%) were malignant, including 487 papillary thyroid…

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