Artificial Intelligence Applied to Osteoporosis: A Performance Comparison of Machine Learning Algorithms in Predicting Fragility Fractures From MRI Data.

ABSTRACT:

Background

A current challenge in osteoporosis is identifying patients at risk of bone fracture.

Purpose

To identify the machine learning classifiers that predict best osteoporotic bone fractures and, from the data, to highlight the imaging features and the anatomical regions that contribute most to prediction performance.

Study type

Prospective (cross-sectional) case-control study.

Population

Thirty-two women with prior fragility bone fractures, of mean age = 61.6 and body mass index (BMI) = 22.7 kg/m² , and 60 women without fractures, of mean age = 62.3 and BMI = 21.4 kg/m² . Field Strength/ Sequence: 3D FLASH at 3T.

Assessment

Quantitative MRI outcomes by software algorithms. Mechanical and topological microstructural parameters

SUBMITTER: Ferizi U 

PROVIDER: S-EPMC7340101 | biostudies-literature | 2019 Apr

REPOSITORIES: biostudies-literature