ReviewJournal of robotic surgery2026
Robotic-assisted and AI-augmented arthroplasty: converging technologies in joint replacement.
Review in Journal of robotic surgery, 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
Technology-enabled total joint arthroplasty has bifurcated into two converging paradigms: robotic-assisted arthroplasty (RAA), dominated by haptic-bounded semi-active arms, and AI-augmented arthroplasty (AIAA), propelled by computer vision, machine-learning analytics, and sensor-based implants. While both aim to eliminate alignment outliers and improve patient satisfaction, their comparative advantages, limitations, and synergistic trajectory remain incompletely synthesised. This narrative review evaluated peer-reviewed and grey literature published between 2019 and May 2025, retrieved from seven bibliographic databases, regulatory filings, and conference proceedings. In total, 1,529 records were identified and screened (1,482 from databases and 47 from grey literature). Eighty-three studies meeting predefined inclusion criteria were included in the narrative synthesis. Recent AI-guided vision systems report coronal alignment accuracy approaching that of semi-active robotic platforms, suggesting narrowing technical differentials. AI-guided workflows demonstrated earlier return to functional milestones and comparable patient-reported outcomes to conventional techniques at one year, while robots retained advantages in severe deformities. Smart-implant telemetry coupled with deep-learning alerts has shown preliminary signals of reduced early dislocation rates in hip cohorts, although long-term comparative outcome data across healthcare systems remain scarce. Preliminary cost-utility modelling suggests lower capital barriers for software-based AI augmentation, although long-term comparative durability data remain limited. The next generation of intelligent arthroplasty platforms will likely integrate robotic execution with adaptive AI-driven analytics, forming closed-loop surgical ecosystems. Optimal value requires integrated hybrid platforms governed by transparent interoperability standards, carbon-aware procurement, and equitable access frameworks, underpinned by rigorous multicentre trials and multidisciplinary collaboration.
Indexed as
Identifiers
42010083What 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.