Automated machine learning-based prediction of the progression of knee pain, functional decline, and incidence of knee osteoarthritis in individuals at high risk of knee osteoarthritis: Data from the osteoarthritis initiative study.

ABSTRACT:

Objective

This study aimed to examine the performance of machine learning models in predicting the progression of knee pain, functional decline, and incidence of knee osteoarthritis (OA) in high-risk individuals, with automated machine learning (AutoML) being used to automate the prediction process.

Design

There were four stages in the process of our AutoML-integrated prediction. Stage 1-Data preparation: The data of 3200 eligible individuals in the Osteoarthritis Initiative (OAI) study who were considered at high risk of knee OA at the baseline visit were extracted and used. Specifically, 1094 variables from the OAI study were used to predict the changes in knee pain, physical function, and incidence of knee OA (i.e. the first occurrence of frequent knee symptoms and defini

SUBMITTER: Chen T 

PROVIDER: S-EPMC10685797 | biostudies-literature | 2023 Jan-Dec

REPOSITORIES: biostudies-literature