XGBoost-SHAP-based interpretable diagnostic framework for knee osteoarthritis: a population-based retrospective cohort study
Abstract Objective To use routine demographic and clinical data to develop an interpretable individual-level machine learning (ML) model to diagnose knee osteoarthritis (KOA) and to identify highly ranked features. Methods In this retrospective, population-based cohort study, anonymized questionnair...
Main Authors: | , , , , , , , , |
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Format: | Article |
Language: | English |
Published: |
BMC
2024-12-01
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Series: | Arthritis Research & Therapy |
Subjects: | |
Online Access: | https://doi.org/10.1186/s13075-024-03450-2 |