Evaluation of the performance of traditional machine learning algorithms, convolutional neural network and AutoML Vision in ultrasound breast lesions classification: a comparative study.

ABSTRACT:

Background

In recent years, there was an increasing popularity in applying artificial intelligence in the medical field from computer-aided diagnosis (CAD) to patient prognosis prediction. Given the fact that not all healthcare professionals have the required expertise to develop a CAD system, the aim of this study was to investigate the feasibility of using AutoML Vision, a highly automatic machine learning model, for future clinical applications by comparing AutoML Vision with some commonly used CAD algorithms in the differentiation of benign and malignant breast lesions on ultrasound.

Methods

A total of 895 breast ultrasound images were obtained from the two online open-access ultrasound breast images datasets. Traditional machine learning models (comprising of seven comm

SUBMITTER: Wan KW 

PROVIDER: S-EPMC7930687 | biostudies-literature | 2021 Apr

REPOSITORIES: biostudies-literature