Endocrine Abstracts

Evaluation of learning methods similar to deep learning and device using deep learning for the diagnosis of thyroid nodules.BackgroundWe recently developed a deep convolutional neural network algorithm (SEveRance Artificial intelligence program, SERA) using 13,560 ultrasonography images of thyroid nodules labeled benign and malignant and this algorithm showed comparable diagnostic performance with experienced radiologists. We wondered whether this self-learning method of SERA ...

Objective: The purpose of this study is to evaluate and compare the effectiveness of artificial intelligence-based computer-assisted diagnosis (AI-CAD) in diagnosing thyroid malignancy by inexperienced physicians and experienced radiologist.Methods: A total of 201 thyroid nodules from 192 patients was simultaneously evaluated by physician and radiologist using real-time ultrasound. After implementing AI-CAD, they reassessed the thyroid nodules. If necess...

Objective: Improved molecular testing for common somatic mutations and the identification of mRNA and microRNA expression classifiers are promising approaches for the diagnosis of thyroid nodules. However, there is a need to improve the diagnostic accuracy of such tests in identifying thyroid cancer. Recent findings have revealed a crucial role of lncRNAs in gene modulation. Thus, we aimed to evaluate the diagnostic value of selected lncRNAs from The Atlas of Noncoding RNAs in...