ReviewCurrent rheumatology reports2023
Machine Learning Approaches to the Prediction of Osteoarthritis Phenotypes and Outcomes.
Review in Current rheumatology reports, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 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
13 citing papers in PubMed, 16 citations in OpenAlex.
- Elucidating the mechanism of taurine in alleviating osteoarthritis progression based on bioinformatics, machine learning algorithm, and experimental validation.Arthritis research & therapy · 2026Article
- Development of Machine Learning Algorithms Predicting Psychological Distress After Total Joint Arthroplasty.The Journal of arthroplasty · 2026Article
- RBP4-a risk factor in lipid metabolism-serves as an early diagnostic and prognostic marker of knee osteoarthritis progression.Arthritis research & therapy · 2026Article
- Artificial intelligence and big data for precision regenerative medicine in knee osteoarthritis: endotyping, responder prediction, and clinical translation.Frontiers in bioengineering and biotechnology · 2026Review
- Review
- Patterns of Shared Variation in Knee Ultrasound for Osteoarthritis: A Machine Learning Approach.Osteoarthritis imaging · 2025Article
- Rethinking arthritis: exploring its types and emerging management strategies.Inflammopharmacology · 2025Review
- Integrating bioinformatics and machine learning to identify biomarkers of branched chain amino acid related genes in osteoarthritis.BMC musculoskeletal disorders · 2025Article
- Constructing machine learning-based risk prediction model for osteoarthritis in population aged 45 and above: NHANES 2011-2018.Scientific reports · 2025Article
- Therapeutic Controlled Release Strategies for Human Osteoarthritis.Advanced healthcare materials · 2025Review
- Identifying trajectories of joint space width loss among previously injured knees: Data from the Osteoarthritis Initiative.PloS one · 2025Article
- Clinical phenotypes, molecular endotypes and theratypes in OA therapeutic development.Nature reviews. Rheumatology · 2024Article
- Artificial intelligence in planned orthopaedic care.SICOT-J · 2024Article
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 1 institution in 1 country.
Funding
Abstract
purpose of reviewOsteoarthritis (OA) is a complex heterogeneous disease with no effective treatments. Artificial intelligence (AI) and its subfield machine learning (ML) can be applied to data from different sources to (1) assist clinicians and patients in decision making, based on machine-learned evidence, and (2) improve our understanding of pathophysiology and mechanisms underlying OA, providing new insights into disease management and prevention. The purpose of this review is to improve the ability of clinicians and OA researchers to understand the strengths and limitations of AI/ML methods in applications to OA research. RECENT
findingsAI/ML can assist clinicians by prediction of OA incidence and progression and by providing tailored personalized treatment. These methods allow using multidimensional multi-source data to understand the nature of OA, to identify different OA phenotypes, and for biomarker discovery. We described the recent implementations of AI/ML in OA research and highlighted potential future directions and associated challenges.
Indexed as
Identifiers
What Socratic 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 Socratic graph.