ReviewSkeletal radiology2022
AI MSK clinical applications: cartilage and osteoarthritis.
Review in Skeletal radiology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 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
25 citing papers in PubMed, 35 citations in OpenAlex.
- Validation of an AI-based automated Knee Inflammation MRI Scoring System for assessing bone marrow lesions.EULAR rheumatology open · 2026Article
- AI in Musculoskeletal Imaging: An End-to-End Perspective.Journal of clinical medicine · 2026Review
- Deep learning-based multiclass classification for the diagnosis of hand arthritis on digital radiography: a multicenter study.Frontiers in medicine · 2026Article
- Artificial intelligence in osteoarthritis research: summary of the 2025 OARSI pre-congress workshop.Osteoarthritis and cartilage open · 2025Article
- Evaluation of AI Performance in Spinal Radiographic Measurements Compared to Radiologists: A Study of Accuracy and Efficiency.Journal of imaging · 2025Article
- Machine learning models for clinical and structural knee osteoarthritis prediction: Recent advancements and future directions.Osteoarthritis and cartilage open · 2025Article
- Estimation of time-to-total knee replacement surgery with multimodal modeling and artificial intelligence.Computers in biology and medicine · 2025Article
- Quantitative ultrasound classification of healthy and chemically degraded ex-vivo cartilage.Scientific reports · 2025Article
- Ultrasound-assessed thigh fat thickness is valid for estimating body fat percentage in Division I collegiate female athletes.Journal of science and medicine in sport · 2025Article
- Diagnostic Performance of an Artificial Intelligence Software for the Evaluation of Bone X-Ray Examinations Referred from the Emergency Department.Diagnostics (Basel, Switzerland) · 2025Article
- Can Artificial Intelligence Reliably and Accurately Measure Lower Limb Alignment: A Systematic Review and Meta-Analysis.The archives of bone and joint surgery · 2025Review
- Bone marrow lesions in osteoarthritis: Characterising genetic and histological changes to understand disease pathophysiology.Osteoarthritis and cartilage open · 2024Review
- Deep learning to combat knee osteoarthritis and severity assessment by using CNN-based classification.BMC musculoskeletal disorders · 2024Article
- Clinical validation of fully automated laminar knee cartilage transverse relaxation time (T2) analysis in anterior cruciate ligament (ACL)-injured knees- on behalf of the osteoarthritis (OA)-Bio consortium.Quantitative imaging in medicine and surgery · 2024Article
- Quantitative and Compositional MRI of the Articular Cartilage: A Narrative Review.Tomography (Ann Arbor, Mich.) · 2024Review
- AI applications in musculoskeletal imaging: a narrative review.European radiology experimental · 2024Review
- Quantitative measurement of cartilage morphology in osteoarthritis: current knowledge and future directions.Skeletal radiology · 2023Review
- Imaging of early-stage osteoarthritis: the needs and challenges for diagnosis and classification.Skeletal radiology · 2023Article
- Artificial intelligence in knee osteoarthritis: A comprehensive review for 2022.Osteoarthritis imaging · 2023Article
- LigaNET: A multi-modal deep learning approach to predict the risk of subsequent anterior cruciate ligament injury after surgery.medRxiv : the preprint server for health sciences · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors at 2 institutions in 1 country.
Funding
Abstract
The advancements of artificial intelligence (AI) for osteoarthritis (OA) applications have been rapid in recent years, particularly innovations of deep learning for image classification, lesion detection, cartilage segmentation, and prediction modeling of future knee OA development. This review article focuses on AI applications in OA research, first describing machine learning (ML) techniques and workflow, followed by how these algorithms are used for OA classification tasks through imaging and non-imaging-based ML models. Deep learning applications for OA research, including analysis of both radiographs for automatic detection of OA severity, and MR images for detection of cartilage/meniscus lesions and cartilage segmentation for automatic T
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.