Evidence map›Paper›PMID 41300942›Full record

ReviewDiagnostics (Basel, Switzerland)2025

Artificial Intelligence for the Diagnosis and Management of Patellofemoral Instability: A Comprehensive Review.

Michele Mercurio, Federica Denami, Andrea Vescio, Filippo Familiari, Umile Giuseppe Longo, Olimpio Galasso, Giorgio Gasparini, Italian Orthopaedic Research Society (IORS), David H Dejour

Abstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in Diagnostics (Basel, Switzerland), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Review
  2. 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

9 authors.

Michele MercurioDepartment of Orthopaedic and Trauma Surgery, Magna Graecia University, "Renato Dulbecco" University Hospital, 88100 Catanzaro, Italy.ORCID 0000-0002-8742-5612
Federica DenamiDepartment of Orthopaedic and Trauma Surgery, Magna Graecia University, "Renato Dulbecco" University Hospital, 88100 Catanzaro, Italy.
Andrea VescioDepartment of Orthopaedic and Trauma Surgery, Magna Graecia University, "Renato Dulbecco" University Hospital, 88100 Catanzaro, Italy.ORCID 0000-0002-1677-927X
Filippo FamiliariDepartment of Orthopaedic and Trauma Surgery, Magna Graecia University, "Renato Dulbecco" University Hospital, 88100 Catanzaro, Italy.ORCID 0000-0002-3453-2043
Umile Giuseppe LongoFondazione Policlinico Universitario Campus Bio-Medico, 00128 Roma, Italy.ORCID 0000-0003-4063-9821
Olimpio GalassoDepartment of Medicine, Surgery and Dentistry, University of Salerno, 84081 Salerno, Italy.
Giorgio GaspariniDepartment of Orthopaedic and Trauma Surgery, Magna Graecia University, "Renato Dulbecco" University Hospital, 88100 Catanzaro, Italy.ORCID 0000-0002-8256-7697
Italian Orthopaedic Research Society (IORS)
David H DejourLyon Ortho Clinic, Clínica de la Sauvegarde, 69009 Lyon, France.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Patellofemoral instability (PFI) is a multifactorial orthopedic condition affecting predominantly young and active individuals. Accurate diagnosis and personalized treatment planning remain challenging due to the complex interplay of anatomical and biomechanical factors. Recently, artificial intelligence (AI), particularly machine learning (ML) and deep learning (DL), has gained attention for its role in musculoskeletal imaging and orthopedics care. This review explores the current and potential applications of AI in diagnosis and management of PFI. A total of 11 relevant articles were identified and included in the review. Articles originated from six countries, with China having the most contributions (

Indexed as

artificial intelligenceCTdeep learningmachine learningMRIpatellofemoral instabilityRx

Identifiers

PMID41300942
PMCPMC12650906

What OpenQuestion holds

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LicenceCC BY
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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.