Evidence map›Paper›PMID 41563474›Full record

ReviewOrthopadie (Heidelberg, Germany)2026

[Artificial intelligence in spinal surgery: current applications and future perspectives].

Filip Milicevic, Mohamad Agha Mahmoud, Maher Ghandour, Moh'd Yazan Khasawneh, Amir R Ghasemi, Koroush Kabir, Ümit Mert

Abstract readEnglish AbstractReview
PubMed Publisher
In one paragraph

Review in Orthopadie (Heidelberg, Germany), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Filip MilicevicDepartment of Orthopaedics and Trauma Surgery, Helios University Hospital, University Witten/Herdecke, Heusnerstr. 40, 42283, Wuppertal, Deutschland.
Mohamad Agha MahmoudDepartment of Orthopaedics and Trauma Surgery, Helios University Hospital, University Witten/Herdecke, Heusnerstr. 40, 42283, Wuppertal, Deutschland.
Maher GhandourDepartment of Orthopaedics and Trauma Surgery, Helios University Hospital, University Witten/Herdecke, Heusnerstr. 40, 42283, Wuppertal, Deutschland.
Moh'd Yazan KhasawnehDepartment of Orthopaedics and Trauma Surgery, Helios University Hospital, University Witten/Herdecke, Heusnerstr. 40, 42283, Wuppertal, Deutschland.
Amir R GhasemiDepartment of Orthopaedics and Trauma Surgery, Helios University Hospital, University Witten/Herdecke, Heusnerstr. 40, 42283, Wuppertal, Deutschland.
Koroush KabirDepartment of Orthopaedics and Trauma Surgery, Helios University Hospital, University Witten/Herdecke, Heusnerstr. 40, 42283, Wuppertal, Deutschland.
Ümit MertDepartment of Orthopaedics and Trauma Surgery, Helios University Hospital, University Witten/Herdecke, Heusnerstr. 40, 42283, Wuppertal, Deutschland. Uemit.baran.mert@gmail.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundSpinal surgery is a highly complex field increasingly shaped by digital innovation. Artificial intelligence (AI) and machine learning (ML) offer new opportunities to enhance diagnostics, surgical planning, intraoperative precision, and postoperative care.

methodsA narrative review was conducted based on a selective literature search in PubMed, Scopus, and Google Scholar. Included were peer-reviewed studies from the past 15 years focusing on clinically relevant AI applications across pre-, intra-, and postoperative phases of spinal surgery.

resultsIn the preoperative setting, AI supports history taking, imaging analysis (e.g., automated segmentation, fracture detection, scoliosis measurement), and personalized risk stratification. Intraoperatively, AI facilitates navigation, 3D reconstruction, augmented reality (AR) integration, and robotic assistance. Postoperatively, ML models predict complications, readmissions, and reherniations and assist with telemonitoring. Many systems are still in validation stages.

conclusionArtificial intelligence has the potential to fundamentally transform spinal surgery through increased precision, efficiency, and individualized decision support. Successful clinical integration requires validated algorithms, interdisciplinary collaboration, and ethical frameworks.

Indexed as

Artificial IntelligenceSpinal DiseasesSpineSurgery, Computer-AssistedAugmented RealityForecastingHumansIntelligent SystemsMachine LearningRobotic Surgical ProceduresSoft ComputingAugmented realityMachine learningPostoperative complicationsRobotic surgerySurgical navigation

Identifiers

PMID41563474

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.