20 citations · 30 across the 2 of their papers we have counts for
2 papers
eess.IV2022★ 20 cited
Deep Learning for Classification of Thyroid Nodules on Ultrasound: Validation on an Independent Dataset
Jingxi Weng, Benjamin Wildman-Tobriner, Mateusz Buda +7
Objectives: The purpose is to apply a previously validated deep learning algorithm to a new thyroid nodule ultrasound image dataset and compare its performances with radiologists.…
eess.IV2022★ 10 cited
Multistep Automated Data Labelling Procedure (MADLaP) for Thyroid Nodules on Ultrasound: An Artificial Intelligence Approach for Automating Image Annotation
Jikai Zhang, Maciej M. Mazurowski, Brian C. Allen +1
Machine learning (ML) for diagnosis of thyroid nodules on ultrasound is an active area of research. However, ML tools require large, well-labelled datasets, the curation of which i…