A Human-Algorithm Integration System for Hip Fracture Detection on Plain Radiography: System Development and Validation Study.

ABSTRACT:

Background

Hip fracture is the most common type of fracture in elderly individuals. Numerous deep learning (DL) algorithms for plain pelvic radiographs (PXRs) have been applied to improve the accuracy of hip fracture diagnosis. However, their efficacy is still undetermined.

Objective

The objective of this study is to develop and validate a human-algorithm integration (HAI) system to improve the accuracy of hip fracture diagnosis in a real clinical environment.

Methods

The HAI system with hip fracture detection ability was developed using a deep learning algorithm trained on trauma registry data and 3605 PXRs from August 2008 to December 2016. To compare their diagnostic performance before and after HAI system assistance using an independent testing dataset, 34 physici

SUBMITTER: Cheng CT 

PROVIDER: S-EPMC7732715 | biostudies-literature | 2020 Nov

REPOSITORIES: biostudies-literature