Evidence map›Paper›PMID 41103258›Full record

ReviewKnee surgery, sports traumatology, arthroscopy : official journal of the ESSKA2025

Artificial intelligence agents in orthopaedics: Concepts, capabilities and the road ahead.

Felix C Oettl, James Pruneski, Balint Zsidai, Yinan Yu, Ting Cong, Robert Feldt, Philipp W Winkler, Michael T Hirschmann, Kristian Samuelsson, ESSKA Artificial Intelligence Working Group

Abstract readReview
In one paragraph

Review in Knee surgery, sports traumatology, arthroscopy : official journal of the ESSKA, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. Review
  5. Artificial intelligence agents in orthopaedics: Concepts, capabilities and the road ahead.Knee surgery, sports traumatology, arthroscopy : official journal of the ESSKA · 2025
    Review
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

10 authors.

Felix C OettlDepartment of Orthopedic Surgery, Balgrist University Hospital, University of Zürich, Zurich, Switzerland.ORCID https://orcid.org/0000-0001-9721-685X
James PruneskiDepartment of Orthopaedic Surgery, Tripler Army Medical Center, Honolulu, Hawaii, USA.ORCID https://orcid.org/0000-0002-8645-9386
Balint ZsidaiSahlgrenska Sports Medicine Center, Gothenburg, Sweden.ORCID https://orcid.org/0000-0002-5697-6577
Yinan YuDepartment of Computer Science and Engineering, Chalmers University of Technology, Gothenburg, Sweden.
Ting CongDepartment of Orthopaedic Surgery, University of Pittsburgh, Pittsburgh, Pennsylvania, USA.
Robert FeldtDepartment of Computer Science and Engineering, Chalmers University of Technology, Gothenburg, Sweden.
Philipp W WinklerDepartment for Orthopaedics and Traumatology, Kepler University Hospital GmbH, Johannes Kepler University Linz, Linz, Austria.
Michael T HirschmannDepartment of Orthopaedic Surgery and Traumatology, Kantonsspital Baselland, Bruderholz, Switzerland.
Kristian SamuelssonSahlgrenska Sports Medicine Center, Gothenburg, Sweden.ORCID https://orcid.org/0000-0001-5383-3370
ESSKA Artificial Intelligence Working Group

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Artificial intelligence (AI) is increasingly used in orthopaedics, yet current models are often limited to narrow, isolated tasks like analysing an X-ray or predicting a single outcome. This paper introduces AI agents-a new class of AI systems designed to overcome these limitations. Unlike traditional AI, agents can autonomously manage complex, multistep processes that mirror the complete patient journey. They can coordinate tasks from initial diagnosis and surgical scheduling to postoperative monitoring and rehabilitation, acting as intelligent assistants for clinical teams. This review explains what distinguishes AI agents from conventional AI, explores their potential applications in orthopaedic practice-including perioperative workflow optimisation, research acceleration and intelligent physician support-and discusses the significant implementation and ethical challenges that must be addressed. For the orthopaedic surgeon, understanding AI agents is becoming essential, as these systems offer a transformative potential to enhance efficiency, improve patient outcomes and shape the future of clinical leadership in a technologically advancing field. LEVEL OF EVIDENCE: Level V.

Indexed as

Artificial IntelligenceOrthopedic ProceduresOrthopedicsHumansagentic AIartificial intelligenceclinical decision supportmedical ethicsmultiagent systemssurgical workflow

Identifiers

PMID41103258
PMCPMC12684344

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.