Articles That Use Artificial Intelligence for Ultrasound: A Reader’s Guide

Author:

Kuang Ming,Hu Hang-Tong,Li Wei,Chen Shu-Ling,Lu Xiao-Zhou

Abstract

Artificial intelligence (AI) transforms medical images into high-throughput mineable data. Machine learning algorithms, which can be designed for modeling for lesion detection, target segmentation, disease diagnosis, and prognosis prediction, have markedly promoted precision medicine for clinical decision support. There has been a dramatic increase in the number of articles, including articles on ultrasound with AI, published in only a few years. Given the unique properties of ultrasound that differentiate it from other imaging modalities, including real-time scanning, operator-dependence, and multi-modality, readers should pay additional attention to assessing studies that rely on ultrasound AI. This review offers the readers a targeted guide covering critical points that can be used to identify strong and underpowered ultrasound AI studies.

Publisher

Frontiers Media SA

Subject

Cancer Research,Oncology

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