External validation of an artificial intelligence multi-label deep learning model capable of ankle fracture classification.

ABSTRACT:

Background

Advances in medical imaging have made it possible to classify ankle fractures using Artificial Intelligence (AI). Recent studies have demonstrated good internal validity for machine learning algorithms using the AO/OTA 2018 classification. This study aimed to externally validate one such model for ankle fracture classification and ways to improve external validity.

Methods

In this retrospective observation study, we trained a deep-learning neural network (7,500 ankle studies) to classify traumatic malleolar fractures according to the AO/OTA classification. Our internal validation dataset (IVD) contained 409 studies collected from Danderyd Hospital in Stockholm, Sweden, between 2002 and 2016. The external validation dataset (EVD) contained 399 studies collected fro

SUBMITTER: Olczak J 

PROVIDER: S-EPMC11451058 | biostudies-literature | 2024 Oct

REPOSITORIES: biostudies-literature