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PreprintCited by 10Retinal Imaging and AnalysisGlaucoma and retinal disordersOphthalmology and Visual Health Research

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

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Kumar, Rahul, Gowda, Chirag, Sekhar, Tejas, Vaja, Swapna, Hage, Tamer, Sporn, Kyle, Waisberg, Ethan, Ong, Joshua +2 more·2025·Journal of Clinical Medicine
DOI 10.20944/preprints202504.2430.v1PMC PMC12156424

Preprint — published as 10.3390/jcm14113669

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Abstract

The integration of artificial intelligence (AI) into musculoskeletal and ocular diagnostics has catalyzed a paradigm shift in precision medicine, enabling the detection of subclinical correlations between ocular biomarkers and systemic musculoskeletal pathologies. Convolutional neural networks (CNNs) and multimodal imaging platforms are poised to decode intricate biomechanical and vascular linkages between these systems, offering non-invasive insights into conditions such as osteoporosis, cervical spine instability, and inflammatory arthritis. Validated studies demonstrate that retinal nerve fiber layer (RNFL) thinning, choroidal thickness variations, and optic nerve microstructural changes detected via optical coherence tomography (OCT) correlate strongly with degenerative spinal conditions and joint instability. Simultaneously, AI-enhanced robotic surgical systems, trained on vast orthopedic datasets, are refining procedural accuracy through real-time intraoperative feedback derived from ocular imaging. This review synthesizes advances in AI-driven diagnostic frameworks, predictive analytics, and robotic interventions, emphasizing their role in bridging ocular and musculoskeletal health.

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  • Advances in miniaturized ultrasonography and low-field MRI systems have enabled robust detection of joint effusion, synovial thickening, and osteophytes.

    “Although subtle cartilage lesions may still be a challenge, advances in miniaturized ultrasonicography (using 5–15 MHz broadband transducers, 20–30 Hz frame rates, synthetic aperture techniques, and wireless connectivity) and emerging low-field MRI systems (0.1–0.5 Tesla) equipped with permanent magnets, optimized pulse sequences, and AI-enhanced reconstruction have enabled surprisingly robust det”

    From Biomarker-Guided Imaging and AI-Augmented Diagnosis of Degenerative Joint Disease (2025) · cites this paper as [132]

    The Data Acquisition section discusses musculoskeletal ultrasound for tendon segmentation and synovitis grading, while Emerging Imaging Technologies and AI Integration discusses 3-tesla MRI for visualizing small joint structures. Neither section addresses whether miniaturized ultrasound or low-field MRI robustly detects joint effusion, synovial thickening, and osteophytes; searches for those findings and the claimed low-field specifications found no supporting passage. Page numbers were not available in our copy. (LLM, conf=0.78)

    Experimental — accuracy not yet measured

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Cited by

Sorted by citations

Authors
Kumar, R., Gowda, C., Sekhar, T., Vaja, S., Hage, T., Sporn, K., Waisberg, E., Ong, J., Zaman, N., & Tavakkoli, A.
Affiliations
  • Rush University Medical Center (US)
  • University of Miami (US)
  • Virginia Tech (US)
  • SUNY Upstate Medical University (US)
  • University of Cambridge (GB)
  • University of Michigan (US)
  • University of Nevada, Reno (US)
Corresponding author
Kumar, Rahul
ORCID
Venue
Journal of Clinical Medicine
Publisher
MDPI AG
Published
2025-04-29
Volume
14
Issue
11
Pages
3669-3669
ISSN
2077-0383 (ISSN-L)
DOI
10.20944/preprints202504.2430.v1
PMC
PMC12156424
OpenAlex
W4410643858
Cited by
10
References
0
Citations by year
2026: 6 · 2025: 4
FWCI
1.58
Type
journal article
Language
en
Open access
Licence
Locations
  • Journal of Clinical Medicine (publishedVersion, cc-by)
  • Preprints.org (acceptedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • VTechWorks (Virginia Tech) (publishedVersion, cc-by)
  • Apollo (University of Cambridge) (submittedVersion, cc-by)
Topics
  • Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Retinal Imaging and Analysis
  • Health Sciences › Medicine › Ophthalmology › Glaucoma and retinal disorders
  • Health Sciences › Medicine › Ophthalmology › Ophthalmology and Visual Health Research
Keywords
artificial intelligence, ocular biomarkers, musculoskeletal disorders, optical coherence tomography, retinal nerve fiber layer thinning, choroidal thickness, osteoporosis, cervical spine instability, inflammatory arthritis, AI-assisted surgery, early disease detection

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