Evidence map›Paper›PMID 40507433›Full record

ReviewJournal of clinical medicine2025

Advancements in Machine Learning for Precision Diagnostics and Surgical Interventions in Interconnected Musculoskeletal and Visual Systems.

Rahul Kumar, Chirag Gowda, Tejas C Sekhar, Swapna Vaja, Tami Hage, Kyle Sporn, Ethan Waisberg, Joshua Ong, Nasif Zaman, Alireza Tavakkoli

Abstract readReview
In one paragraph

Review in Journal of clinical medicine, 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

10 authors.

Rahul KumarRush Medical College, Rush University Medical Center, Chicago, IL 60612, USA.ORCID 0000-0001-8574-2895
Chirag GowdaMiller School of Medicine, University of Miami, Miami, FL 33146, USA.ORCID 0009-0002-8177-2784
Tejas C SekharRush Medical College, Rush University Medical Center, Chicago, IL 60612, USA.ORCID 0000-0003-0848-8365
Swapna VajaRush Medical College, Rush University Medical Center, Chicago, IL 60612, USA.ORCID 0000-0002-4982-3708
Tami HageDepartment of Biological Sciences, Virginia Tech, Blacksburg, VA 24061, USA.
Kyle SpornNorton College of Medicine, SUNY Upstate Medical University, Syracuse, NY 13210, USA.ORCID 0009-0005-5707-9009
Ethan WaisbergDepartment of Clinical Neurosciences, University of Cambridge, Cambridge CB2 0SZ, UK.
Joshua OngDepartment of Ophthalmology and Visual Sciences, Kellogg Eye Center, University of Michigan, Ann Arbor, MI 48105, USA.ORCID 0000-0003-4860-827X
Nasif ZamanDepartment of Computer Science and Engineering, University of Nevada, Reno, NV 89557, USA.ORCID 0000-0003-0120-0939
Alireza TavakkoliDepartment of Computer Science and Engineering, University of Nevada, Reno, NV 89557, USA.ORCID 0000-0001-9460-1269

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Artificial intelligence (AI) is reshaping precision medicine by revealing diagnostic links between ocular biomarkers and systemic musculoskeletal disorders. This review synthesizes clinical evidence on the associations between optical coherence tomography (OCT)-derived parameters, such as retinal nerve fiber layer (RNFL) thinning and choroidal thickness, and conditions including osteoporosis, cervical spine instability, and inflammatory arthritis. The findings, based on an analysis of studies that integrate AI with ocular and musculoskeletal imaging, highlight consistent correlations between ocular microstructural changes and systemic degenerative pathologies. These results suggest that the eye may serve as a non-invasive window into biomechanical dysfunction. This review also discusses the emerging role of AI-assisted surgical systems informed by ocular metrics. Overall, AI-driven ocular analysis offers a promising avenue for early detection and management of musculoskeletal disease, supporting its clinical relevance and interdisciplinary potential.

Indexed as

artificial intelligencechoroidal thicknessconvolutional neural networksdegenerative joint diseasemachine learningmusculoskeletal imagingocular biomarkersoptical coherence tomographyretinal nerve fiber layerspine diagnostics

Identifiers

PMID40507433
PMCPMC12156424

What Socratic 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 Socratic graph.