Multiclass datasets expand neural network utility: an example on ankle radiographs.

ABSTRACT:

Purpose

Artificial intelligence in computer vision has been increasingly adapted in clinical application since the implementation of neural networks, potentially providing incremental information beyond the mere detection of pathology. As its algorithmic approach propagates input variation, neural networks could be used to identify and evaluate relevant image features. In this study, we introduce a basic dataset structure and demonstrate a pertaining use case.

Methods

A multidimensional classification of ankle x-rays (n = 1493) rating a variety of features including fracture certainty was used to confirm its usability for separating input variations. We trained a customized neural network on the task of fracture detection using a state-of-the-art preprocessing and training p

SUBMITTER: Kim S 

PROVIDER: S-EPMC10113347 | biostudies-literature | 2023 May

REPOSITORIES: biostudies-literature