ReviewComputational intelligence and neuroscience2021
Emergence of Deep Learning in Knee Osteoarthritis Diagnosis.
Review in Computational intelligence and neuroscience, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 41 papers, 2 of them syntheses that pooled it.
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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
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Who cites it
41 citing papers in PubMed, 2 syntheses or guidelines pooled it, 125 citations in OpenAlex.
- The value of deep learning-based X-ray techniques in detecting and classifying K-L grades of knee osteoarthritis: a systematic review and meta-analysis.European radiology · 2025Pooled it
- Predicting occupational injury causal factors using text-based analytics: A systematic review.Frontiers in public health · 2022Pooled it
- Multifactorial contributors to knee osteoarthritis identified by Machine Learning and Bayesian network analysis: A cross-sectional study of the Iwaki Health Promotion Project.Osteoarthritis and cartilage open · 2026Article
- Advancing deep learning based knee cartilage segmentation in MRI: Innovations, challenges and applications.Osteoarthritis and cartilage open · 2026Article
- Novel algorithm for knee localization and diagnosis and grading of knee osteoarthritis based on a priori information: data from OAI.BMC medical imaging · 2026Article
- Review of CNN-Based Approaches for Preprocessing, Segmentation and Classification of Knee Osteoarthritis.Diagnostics (Basel, Switzerland) · 2026Review
- Artificial intelligence in the biomechanics of knee osteoarthritis: biomechanical phenotyping, risk stratification, diagnosis, treatment and clinical translation-a narrative review.Frontiers in bioengineering and biotechnology · 2026Review
- Classification of anterior cruciate ligament tears in knee magnetic resonance images using pre-trained model and custom model.Scientific reports · 2025Article
- Bayesian Graphical Models for Multiscale Inference in Medical Image-Based Joint Degeneration Analysis.Diagnostics (Basel, Switzerland) · 2025Review
- Artificial Intelligence Model Assists Knee Osteoarthritis Diagnosis via Determination of K-L Grade.Diagnostics (Basel, Switzerland) · 2025Article
- Optimizing the dynamic treatment regime of outpatient rehabilitation in patients with knee osteoarthritis using reinforcement learning.Journal of neuroengineering and rehabilitation · 2025Article
- Bibliometric analysis of the application of artificial intelligence in orthopedic imaging.Quantitative imaging in medicine and surgery · 2025Article
- Bacterial Species in Engineered Living Materials: Strategies and Future Directions.Microbial biotechnology · 2025Review
- A Review for automated classification of knee osteoarthritis using KL grading scheme for X-rays.Biomedical engineering letters · 2025Review
- Effective Feature Extraction for Knee Osteoarthritis Detection on X-ray Images using Convolutional Neural Networks.Current medical imaging · 2025Article
- Potential of AI-based diagnostic grading system for knee osteoarthritis.Frontiers in medicine · 2025Article
- Enhancing knee osteoarthritis detection with AI, image denoising, and optimized classification methods and the importance of physical therapy methods.PeerJ. Computer science · 2025Article
- Context-Aware Dual-Task Deep Network for Concurrent Bone Segmentation and Clinical Assessment to Enhance Shoulder Arthroplasty Preoperative planning.IEEE open journal of engineering in medicine and biology · 2025Article
- Enhancing knee osteoarthritis diagnosis with DMS: a novel dense multi-scale convolutional neural network approach.Journal of orthopaedic surgery and research · 2024Article
- Automatic knee osteoarthritis severity grading based on X-ray images using a hierarchical classification method.Arthritis research & therapy · 2024Article
Corrections and comments
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Authors and funding
7 authors at 3 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Osteoarthritis (OA), especially knee OA, is the most common form of arthritis, causing significant disability in patients worldwide. Manual diagnosis, segmentation, and annotations of knee joints remain as the popular method to diagnose OA in clinical practices, although they are tedious and greatly subject to user variation. Therefore, to overcome the limitations of the commonly used method as above, numerous deep learning approaches, especially the convolutional neural network (CNN), have been developed to improve the clinical workflow efficiency. Medical imaging processes, especially those that produce 3-dimensional (3D) images such as MRI, possess ability to reveal hidden structures in a volumetric view. Acknowledging that changes in a knee joint is a 3D complexity, 3D CNN has been employed to analyse the joint problem for a more accurate diagnosis in the recent years. In this review, we provide a broad overview on the current 2D and 3D CNN approaches in the OA research field. We reviewed 74 studies related to classification and segmentation of knee osteoarthritis from the Web of Science database and discussed the various state-of-the-art deep learning approaches proposed. We highlighted the potential and possibility of 3D CNN in the knee osteoarthritis field. We concluded by discussing the possible challenges faced as well as the potential advancements in adopting 3D CNNs in this field.
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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.