ArticleCellular and molecular bioengineering2020
Machine Learning Classification of Articular Cartilage Integrity Using Near Infrared Spectroscopy.
Article in Cellular and molecular bioengineering, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
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Who cites it
15 citing papers in PubMed, 36 citations in OpenAlex.
- Ex Vivo Differentiation of Cartilage Degeneration Severity and Subchondral Bone Using Vibroacoustic Signals from Instrument-Tissue Interaction.Sensors (Basel, Switzerland) · 2026Article
- Chromatic differential confocal matrix-based 3D topography and hyperspectral imaging with deep learning for osteoarthritis grading.Biomedical optics express · 2026Article
- Quantitative ultrasound classification of healthy and chemically degraded ex-vivo cartilage.Scientific reports · 2025Article
- Classification of osteoarthritic and healthy cartilage using deep learning with Raman spectra.Scientific reports · 2024Article
- Holistic vibrational spectromics assessment of human cartilage for osteoarthritis diagnosis.Biomedical optics express · 2024Article
- Spatial analysis of the osteoarthritis microenvironment: techniques, insights, and applications.Bone research · 2024Review
- Raman Spectroscopy and Machine Learning Enables Estimation of Articular Cartilage Structural, Compositional, and Functional Properties.Annals of biomedical engineering · 2023Article
- Visible and Near-Infrared Spectroscopy Enables Differentiation of Normal and Early Osteoarthritic Human Knee Joint Articular Cartilage.Annals of biomedical engineering · 2023Article
- Assessment of Ligament Viscoelastic Properties Using Raman Spectroscopy.Annals of biomedical engineering · 2022Article
- Articular cartilage optical properties in the near-infrared (NIR) spectral range vary with depth and tissue integrity.Biomedical optics express · 2021Article
- Vibrational Spectroscopy in Assessment of Early Osteoarthritis-A Narrative Review.International journal of molecular sciences · 2021Review
- Applications of Vibrational Spectroscopy for Analysis of Connective Tissues.Molecules (Basel, Switzerland) · 2021Review
- Characterization of connective tissues using near-infrared spectroscopy and imaging.Nature protocols · 2021Article
- Tissue optical properties combined with machine learning enables estimation of articular cartilage composition and functional integrity.Biomedical optics express · 2020Article
- Early Diagnosis of Type 2 Diabetes Based on Near-Infrared Spectroscopy Combined With Machine Learning and Aquaphotomics.Frontiers in chemistry · 2020Article
Corrections and comments
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Authors and funding
8 authors at 4 institutions in 3 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
introductionAssessment of cartilage integrity during arthroscopy is limited by the subjective visual nature of the technique. To address this shortcoming in diagnostic evaluation of articular cartilage, near infrared spectroscopy (NIRS) has been proposed. In this study, we evaluated the capacity of NIRS, combined with machine learning techniques, to classify cartilage integrity.
methodsRabbit (
resultsThe results show that the model based on SVM is optimal of distinguishing between ACLT and CNTRL samples (ROC_AUC = 0.93, kappa = 0.86), LR is capable of distinguishing between CL and CNTRL samples (ROC_AUC = 0.91, kappa = 0.81), while DNN is optimal for discriminating between the different classes (multi-class classification, kappa = 0.48).
conclusionWe show that NIR spectroscopy, when combined with machine learning techniques, is capable of holistic assessment of cartilage integrity, with potential for accurately distinguishing between healthy and diseased cartilage.
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Registered trials
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.