Evidence map›Paper›PMID 41501582›Full record

ReviewOrthopadie (Heidelberg, Germany)2026

[Artificial intelligence in orthopaedic oncology].

Sebastian Breden, Paulina Seidl, Sarah Consalvo, Ulrich Lenze, Carolin Knebel, Rüdiger von Eisenhart-Rothe, Florian Hinterwimmer

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.

Sebastian BredenKlinik und Poliklinik für Orthopädie und Sportorthopädie, TUM Klinikum München, Ismaninger Str. 22, 81675, München, Deutschland. Sebastian.breden@mri.tum.de.
Paulina SeidlKlinik und Poliklinik für Orthopädie und Sportorthopädie, TUM Klinikum München, Ismaninger Str. 22, 81675, München, Deutschland.
Sarah ConsalvoKlinik und Poliklinik für Orthopädie und Sportorthopädie, TUM Klinikum München, Ismaninger Str. 22, 81675, München, Deutschland.
Ulrich LenzeKlinik und Poliklinik für Orthopädie und Sportorthopädie, TUM Klinikum München, Ismaninger Str. 22, 81675, München, Deutschland.
Carolin KnebelKlinik und Poliklinik für Orthopädie und Sportorthopädie, TUM Klinikum München, Ismaninger Str. 22, 81675, München, Deutschland.
Rüdiger von Eisenhart-RotheKlinik und Poliklinik für Orthopädie und Sportorthopädie, TUM Klinikum München, Ismaninger Str. 22, 81675, München, Deutschland.
Florian HinterwimmerKlinik und Poliklinik für Orthopädie und Sportorthopädie, TUM Klinikum München, Ismaninger Str. 22, 81675, München, Deutschland.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Artificial intelligence (AI) offers new opportunities to enhance diagnostics and therapy planning in orthopaedic oncology-a field marked by the rarity of musculoskeletal tumors and associated clinical challenges. This review presents the current state of AI-based image analysis, segmentation, and prognostic modeling, and highlights key applications including differential diagnosis, surgical planning, and workflow optimization. In addition to outlining the technological foundations, the article addresses limitations, ethical concerns, and essential requirements for successful clinical integration. It aims to provide a realistic perspective on both the potential and the limitations of AI in this specialized domain.

Indexed as

Artificial IntelligenceBone NeoplasmsMedical OncologyOrthopedicsDiagnosis, DifferentialHumansPrognosisDifferential diagnosisImage analysis, computer-assistedMachine learningOsteosarcomaPrognosis

Identifiers

PMID41501582

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.