ReviewJournal of orthopaedic case reports2026
Artificial Intelligence-Guided Precision Orthobiologics in Musculoskeletal Conditions.
Review in Journal of orthopaedic case reports, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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
0 citing papers in PubMed.
No citing paper in PubMed yet.
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.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Introduction: The use of orthobiologics such as autologous peripheral blood-derived orthobiologics, bone marrow-derived biologics, adipose tissue-derived biologics, mesenchymal stem cells, and extracellular vesicles is gaining traction in the field of orthobiology for the treatment of osteoarthritis (OA), tendinopathy, cartilage injuries, and delayed musculoskeletal healing. Clinical responses are inconsistent due to biological variation among patients, disease manifestations, product composition, delivery accuracy, and outcome definitions. Materials and Methods: The literature was searched in PubMed, Embase, Cochrane Library, and Scopus databases from January 2019 to June 2026, and landmark and regulatory concepts were considered. The search terms were orthobiologics, platelet-rich plasma, mesenchymal stromal cells, OA, tendinopathy, artificial intelligence (AI), machine learning, imaging biomarkers, ultrasound guidance, responder prediction, potency assays, software as a medical device and regulation. The synthesis of evidence was done in a narrative fashion based on the Scale for the Assessment of Narrative Review articles principles. Results: AI has the greatest clinical relevance as an enabler for precision orthobiologics. Supervised models can predict responder probability after platelet-rich plasma; unsupervised clustering can identify inflammatory, metabolic, structural, or pain-dominant phenotypes; deep learning can quantify imaging biomarkers; natural language processing can identify longitudinal outcomes; and privacy-preserving learning can facilitate multicenter validation. Product variability may be lessened through parallel advances in cytometry, secretome profiling, potency testing, and image-guided delivery. However, the evidence is still early, largely retrospective, and prone to bias, data drift, poor external validation, and unclear regulatory classification. Conclusion: AI-assisted orthobiologics can be considered as a translational precision-medicine architecture, not a fully formed product. Standardized characterization of the biologic, a prospectively validated prediction model, easily understandable outputs, regulatory alignment, and ongoing monitoring of outcomes before routine clinical use are all necessary for safe implementation.
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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.