Radiologist bests machine-learning algorithms at diagnosing thyroid cancer

In developing algorithms to differentiate between suspicious nodules in the thyroid gland, researchers in China have found that their machine-learning computations separate malignant from benign properties more accurately than an inexperienced radiologist—but not as accurately as the experienced radiologist whose know-how was used to create the algorithms. Their research is running in the October edition of the American Journal of Roentgenology. Dr. Hongxun Wu of Jiangyuan Hospital in the province of Jiangsu and colleagues worked with 970 histopathologically proven thyroid nodules in 970 patients. They had two radiologists retrospectively review ultrasound images of the nodules, grading them according to a five-tier scoring system. One of the rads—the one whose clinical interpretations would feed the computations—had 17 years of experience. The other had three. The team then obtained statistically significant nodule…


Link to Full Article: Radiologist bests machine-learning algorithms at diagnosing thyroid cancer