Endocrine Tumor Classification via Machine-Learning-Based Elastography: A Systematic Scoping Review.

ABSTRACT: Elastography complements traditional medical imaging modalities by mapping tissue stiffness to identify tumors in the endocrine system, and machine learning models can further improve diagnostic accuracy and reliability. Our objective in this review was to summarize the applications and performance of machine-learning-based elastography on the classification of endocrine tumors. Two authors independently searched electronic databases, including PubMed, Scopus, Web of Science, IEEEXpress, CINAHL, and EMBASE. Eleven (n = 11) articles were eligible for the review, of which eight (n = 8) focused on thyroid tumors and three (n = 3) considered pancreatic tumors. In all thyroid studies, the researchers used shear-wave ultrasound elastography, whereas the pancreas researchers

SUBMITTER: Mao YJ 

PROVIDER: S-EPMC9913672 | biostudies-literature | 2023 Jan

REPOSITORIES: biostudies-literature