ReviewJournal of robotic surgery2025
Revolutionizing spine surgery with emerging AI-FEA integration.
Review in Journal of robotic surgery, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 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
7 citing papers in PubMed.
- Artificial Intelligence for Clinical Decision Support in Rural Spine Care: A Narrative Review.Healthcare (Basel, Switzerland) · 2026Review
- Large Language Model Hallucinations in Spine Surgery: A Comparative Analysis of Clinician vs Patient-Level Prompts.Neurosurgery practice · 2026Article
- Digital Twins in Orthopedics and Trauma: Concepts, Emerging Evidence, and Barriers to Clinical Translation.Journal of clinical medicine · 2026Review
- Digital twins and multimodal artificial intelligence in spine care: a scoping review of concepts, evidence, and translational barriers.Spine deformity · 2026Review
- Percutaneous spinal endoscopic surgery for thoracic ossification of the posterior longitudinal ligament: a noval bilateral crossover decompression technique.Journal of orthopaedic surgery and research · 2026Article
- Review
- A Review of Finite Element Analysis in Spine Surgery Decision-Making.Journal of clinical medicine · 2026Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
12 authors.
Funding
Abstract
This study explores the integration of artificial intelligence (AI) and finite element analysis (FEA) in spine surgery, highlighting their complementary roles across preoperative planning, intraoperative execution, and postoperative outcome prediction. The synergy between AI and FEA is reshaping modern spine care by improving biomechanical modeling, enhancing surgical precision, and enabling personalized treatment strategies. In the preoperative phase, AI-augmented FEA supports the design of patient-specific surgical plans, optimizing implant placement and simulating mechanical responses under various loading conditions. Intraoperatively, AI enables real-time image-guided navigation, robotic assistance, and automated anatomical recognition, reducing the risk of surgical error. Postoperatively, predictive models built on FEA simulations and patient data assist in tracking recovery, forecasting complications, and informing rehabilitation protocols. Together, these technologies contribute to a data-driven paradigm shift toward precision spine surgery. As intelligent feedback systems, digital twins, and autonomous surgical platforms continue to evolve, AI-FEA integration is poised to play a transformative role in delivering safer, more efficient, and individualized spine care.
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.