ArticleDiagnostics (Basel, Switzerland)2021
Prediction of Joint Space Narrowing Progression in Knee Osteoarthritis Patients.
Article in Diagnostics (Basel, Switzerland), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
10 citing papers in PubMed, 32 citations in OpenAlex.
- Predicting Knee osteoarthritis progression using explainable machine learning and clinical imaging data.Osteoarthritis and cartilage open · 2026Article
- Clinical efficacy of unicompartmental knee arthroplasty on limb swelling, pain, and functional rehabilitation in knee osteoarthritis patients.Journal of orthopaedic surgery and research · 2025Article
- Article
- A comprehensive patient-specific prediction model for temporomandibular joint osteoarthritis progression.Proceedings of the National Academy of Sciences of the United States of America · 2024Article
- Improved Prediction of Knee Osteoarthritis by the Machine Learning Model XGBoost.Indian journal of orthopaedics · 2023Article
- Adversarial Evolving Neural Network for Longitudinal Knee Osteoarthritis Prediction.IEEE transactions on medical imaging · 2022Article
- Development and Evaluation of a Machine Learning Prediction Model for Small-for-Gestational-Age Births in Women Exposed to Radiation before Pregnancy.Journal of personalized medicine · 2022Article
- Explainable machine learning for knee osteoarthritis diagnosis based on a novel fuzzy feature selection methodology.Physical and engineering sciences in medicine · 2022Article
- An Explainable Machine Learning Approach for COVID-19's Impact on Mood States of Children and Adolescents during the First Lockdown in Greece.Healthcare (Basel, Switzerland) · 2022Article
- Discovering Knee Osteoarthritis Imaging Features for Diagnosis and Prognosis: Review of Manual Imaging Grading and Machine Learning Approaches.Journal of healthcare engineering · 2022Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 2 institutions in 1 country.
Funding
Abstract
Osteoarthritis is a joint disease that commonly occurs in the knee (KOA). The continuous increase in medical data regarding KOA has triggered researchers to incorporate artificial intelligence analytics for KOA prognosis or treatment. In this study, two approaches are presented to predict the progression of knee joint space narrowing (JSN) in each knee and in both knees combined. A machine learning approach is proposed with the use of multidisciplinary data from the osteoarthritis initiative database. The proposed methodology employs: (i) A clustering process to identify groups of people with progressing and non-progressing JSN; (ii) a robust feature selection (FS) process consisting of filter, wrapper, and embedded techniques that identifies the most informative risk factors; (iii) a decision making process based on the evaluation and comparison of various classification algorithms towards the selection and development of the final predictive model for JSN; and (iv) post-hoc interpretation of the features' impact on the best performing model. The results showed that bounding the JSN progression of both knees can result to more robust prediction models with a higher accuracy (83.3%) and with fewer risk factors (29) compared to the right knee (77.7%, 88 risk factors) and the left knee (78.3%, 164 risk factors), separately.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.