Modeling and predicting osteoarthritis progression: data from the osteoarthritis initiative

Regression shrinkage and selection via the lasso

Tibshirani, R. (1996) · Journal of the Royal Statistical Society Series B: Statistical Methodology · doi:10.1111/j.2517-6161.1996.tb02080.x · Cited by 51,482 · see citing works

The Elements of Statistical Learning

Hastie, T., Friedman, J., & Tibshirani, R. (2001) · Springer Series in Statistics · doi:10.1007/978-0-387-21606-5 · Cited by 24,162 · see citing works

Silhouettes: A graphical aid to the interpretation and validation of cluster analysis

Rousseeuw, P. J. (1987) · Journal of Computational and Applied Mathematics · doi:10.1016/0377-0427(87)90125-7 · Cited by 21,392 · see citing works

Analyzing developmental trajectories: A semiparametric, group-based approach.

Nagin, D. S. (1999) · Psychological Methods · doi:10.1037/1082-989x.4.2.139 · Cited by 2,346 · see citing works

Risk factors for onset of osteoarthritis of the knee in older adults: a systematic review and meta-analysis

Blagojevic, M., Jinks, C., Jeffery, A., & Jordan, K. P. (2009) · Osteoarthritis and Cartilage · doi:10.1016/j.joca.2009.08.010 · Cited by 1,399 · see citing works

Analyzing developmental trajectories of distinct but related behaviors: A group-based method.

Nagin, D. S., & Tremblay, R. E. (2001) · Psychological Methods · doi:10.1037/1082-989x.6.1.18 · Cited by 1,283 · see citing works

Pathogenesis and management of pain in osteoarthritis

Dieppe, P. A., & Lohmander, S. L. (2005) · The Lancet · doi:10.1016/s0140-6736(05)71086-2 · Cited by 1,214 · see citing works

Bone Marrow Edema and Its Relation to Progression of Knee Osteoarthritis

Felson, D. T., McLaughlin, S., Goggins, J., LaValley, M. P., Gale, M. E., Totterman, S. M. S., Li, W., Hill, C. L., & Gale, D. R. (2003) · Annals of Internal Medicine · doi:10.7326/0003-4819-139-5_part_1-200309020-00008 · Cited by 757 · see citing works

Osteo-Arthrosis: Prevalence in the Population and Relationship between Symptoms and X-ray Changes

Lawrence, J. S., Bremner, J. M., & Bier, F. (1966) · Annals of the Rheumatic Diseases · doi:10.1136/ard.25.1.1 · Cited by 676 · see citing works

Bone Mineral Acquisition in Healthy Asian, Hispanic, Black, and Caucasian Youth: A Longitudinal Study1

Bachrach, L. K., Hastie, T. J., Wang, M., Narasimhan, B., & Marcus, R. (1999) · The Journal of Clinical Endocrinology & Metabolism · doi:10.1210/jcem.84.12.6182 · Cited by 533 · see citing works

Clustering for Sparsely Sampled Functional Data

James, G. M., & Sugar, C. A. (2003) · Journal of the American Statistical Association · doi:10.1198/016214503000189 · Cited by 521 · see citing works

Principal component models for sparse functional data

James, G. M. (2000) · Biometrika · doi:10.1093/biomet/87.3.587 · Cited by 462 · see citing works

Association between radiographic features of knee osteoarthritis and pain: results from two cohort studies

Neogi, T., Felson, D. T., Niu, J., Nevitt, M. C., Lewis, C. E., Aliabadi, P., Sack, B., Torner, J. C., Bradley, L. A., & Zhang, Y. (2009) · BMJ · doi:10.1136/bmj.b2844 · Cited by 460 · see citing works

Bone Mineral Acquisition in Healthy Asian, Hispanic, Black, and Caucasian Youth: A Longitudinal Study

Bachrach, L. K. (1999) · The Journal of Clinical Endocrinology & Metabolism · doi:10.1210/jc.84.12.4702 · Cited by 340 · see citing works

Functional Linear Discriminant Analysis for Irregularly Sampled Curves

James, G. M., & Hastie, T. J. (2001) · Journal of the Royal Statistical Society Series B (Statistical Methodology) · doi:10.1111/1467-9868.00297 · Cited by 312 · see citing works

The Bristol ‘OA500’ Study: progression of osteoarthritis (OA) over 3 years and the relationship between clinical and radiographic changes at the knee joint

Dieppe, P. A., Cushnaghan, J., & Shepstone, L. (1997) · Osteoarthritis and Cartilage · doi:10.1016/s1063-4584(97)80002-7 · Cited by 263 · see citing works

Trajectories and risk profiles of pain in persons with radiographic, symptomatic knee osteoarthritis: data from the osteoarthritis initiative

Collins, J. E., Katz, J. N., Dervan, E. E., & Losina, E. (2014) · Osteoarthritis and Cartilage · doi:10.1016/j.joca.2014.03.009 · Cited by 251 · see citing works

Associations between pain, function, and radiographic features in osteoarthritis of the knee

Szebenyi, B., Hollander, A. P., Dieppe, P. A., Quilty, B., Duddy, J., Clarke, S., & Kirwan, J. (2005) · Arthritis & Rheumatism · doi:10.1002/art.21534 · Cited by 217 · see citing works

Association of pain with radiological changes in different compartments and views of the knee joint

Cicuttini, F., Baker, J., Hart, D. J., & Spector, T. D. (1996) · Osteoarthritis and Cartilage · doi:10.1016/s1063-4584(05)80323-1 · Cited by 194 · see citing works

Association of radiographic features of osteoarthritis of the knee with knee pain: Data from the baltimore longitudinal study of aging

Lethbridge‐Çejku, M., Scott, W. W., Reichle, R., Ettinger, W. H., Zonderman, A. B., Costa, P. T., Plato, C. C., Tobin, J. D., & Hochberg, M. C. (1995) · Arthritis & Rheumatism · doi:10.1002/art.1790080311 · Cited by 174 · see citing works

Pain mechanisms in osteoarthritis of the knee: effect of intraarticular anesthetic.

Creamer, P., Hunt, M., & Dieppe, P. A. (1996) · PubMed · Cited by 167 · see citing works

Trainable rule‐based algorithm for the measurement of joint space width in digital radiographic images of the knee

Duryea, J., Li, J., PETERFY, C. G., Gordon, C., & Genant, H. K. (2000) · Medical Physics · doi:10.1118/1.598897 · Cited by 139 · see citing works

CHECK (Cohort Hip and Cohort Knee): similarities and differences with the Osteoarthritis Initiative

Wesseling, J., Dekker, J., van den Berg, W. B., Bierma‐Zeinstra, S., Boers, M., Cats, H. A., Deckers, P., Gorter, K. J., Heuts, P. H. T. G., Hilberdink, W. K. H. A., et al. (2008) · Annals of the Rheumatic Diseases · doi:10.1136/ard.2008.096164 · Cited by 136 · see citing works

Pain trajectory groups in persons with, or at high risk of, knee osteoarthritis: findings from the Knee Clinical Assessment Study and the Osteoarthritis Initiative

Nicholls, E. E., Thomas, E., van der Windt, D., Croft, P. R., & Peat, G. (2014) · Osteoarthritis and Cartilage · doi:10.1016/j.joca.2014.09.026 · Cited by 120 · see citing works

Is osteoarthritis a heterogeneous disease that can be stratified into subsets?

Driban, J. B., Sitler, M. R., Barbe, M. F., & Balasubramanian, E. (2009) · Clinical Rheumatology · doi:10.1007/s10067-009-1301-1 · Cited by 119 · see citing works

Location specific radiographic joint space width for osteoarthritis progression

Neumann, G., Hunter, D. J., Nevitt, M. C., Chibnik, L. B., Kwoh, K. C., Chen, H. A., Harris, T. B., Satterfield, S., & Duryea, J. (2008) · Osteoarthritis and Cartilage · doi:10.1016/j.joca.2008.11.001 · Cited by 110 · see citing works

Identifying Trajectories of Pain Severity in Early Symptomatic Knee Osteoarthritis: A 5-year Followup of the Cohort Hip and Cohort Knee (CHECK) Study

Wesseling, J., Bastick, A. N., ten Wolde, S., Kloppenburg, M., Lafeber, F. P. J. G., Bierma‐Zeinstra, S., & Bijlsma, J. W. J. (2015) · The Journal of Rheumatology · doi:10.3899/jrheum.141036 · Cited by 59 · see citing works

Defining discriminative pain trajectories in hip osteoarthritis over a 2-year time period

Verkleij, S. P., Hoekstra, T., Rozendaal, R. M., Waarsing, J. H., Koes, B. W., Luijsterburg, P. A. J., & Bierma‐Zeinstra, S. (2012) · Annals of the Rheumatic Diseases · doi:10.1136/annrheumdis-2011-200687 · Cited by 58 · see citing works

Structural Associations of Osteoarthritis Pain: Lessons from Magnetic Resonance Imaging

Conaghan, P. G., & Felson, D. T. (2004) · Novartis Foundation symposium · doi:10.1002/0470867639.ch13 · Cited by 40 · see citing works

Defining hip pain trajectories in early symptomatic hip osteoarthritis – 5 year results from a nationwide prospective cohort study (CHECK)

Bastick, A. N., Verkleij, S. P., Damen, J., Wesseling, J., Hilberdink, W. K., Bindels, P., & Bierma-Zeinstra, S. M. (2016) · Osteoarthritis and Cartilage · doi:10.1016/j.joca.2015.11.023 · Cited by 34 · see citing works

Forecasting the future pain in hip OA: can we rely on pain trajectories?

Losina, E., & Collins, J. E. (2016) · Osteoarthritis and Cartilage · doi:10.1016/j.joca.2016.01.989 · Cited by 12 · see citing works

Modeling longitudinal osteoarthritis data to identify homogeneous subgroups: opportunities and challenges in a burgeoning literature

Riddle, D. L., & Dumenci, L. (2015) · Osteoarthritis and Cartilage · doi:10.1016/j.joca.2015.02.777 · Cited by 11 · see citing works

Machine learning in knee osteoarthritis: A review

Kokkotis, C., Moustakidis, S., Papageorgiou, E. I., Giakas, G., & Tsaopoulos, D. E. (2020) · Osteoarthritis and Cartilage Open · doi:10.1016/j.ocarto.2020.100069 · Cited by 157 · see citing works

A deep learning method for predicting knee osteoarthritis radiographic progression from MRI

Schiratti, J.-B., Dubois, R., Hérent, P., Cahané, D., Dachary, J., Clozel, T., Wainrib, G., Keime-Guibert, F., Lalande, A., Pueyo, M. E., et al. (2021) · Arthritis Research & Therapy · doi:10.1186/s13075-021-02634-4 · Cited by 107 · see citing works

AI applications in musculoskeletal imaging: a narrative review

Gitto, S., Serpi, F., Albano, D., Risoleo, G., Fusco, S., Messina, C., & Sconfienza, L. M. (2024) · European Radiology Experimental · doi:10.1186/s41747-024-00422-8 · Cited by 103 · see citing works

Deep learning approach to predict pain progression in knee osteoarthritis

Guan, B., Liu, F., Mizaian, A. H., Demehri, S., Samsonov, A. A., Guermazi, A., & Kijowski, R. (2021) · Skeletal Radiology · doi:10.1007/s00256-021-03773-0 · Cited by 99 · see citing works

Molecular Classification of Knee Osteoarthritis

Lv, Z., Yang, Y., Li, J.-W., Fei, Y.-X., Guo, H., Sun, Z.-Y., Lu, J., Xu, X.-Q., Jiang, Q., Ikegawa, S., et al. (2021) · Frontiers in Cell and Developmental Biology · doi:10.3389/fcell.2021.725568 · Cited by 93 · see citing works

Deep learning risk assessment models for predicting progression of radiographic medial joint space loss over a 48-MONTH follow-up period

Guan, B., Liu, F., Haj‐Mirzaian, A., Demehri, S., Samsonov, A. A., Neogi, T., Guermazi, A., & Kijowski, R. (2020) · Osteoarthritis and Cartilage · doi:10.1016/j.joca.2020.01.010 · Cited by 67 · see citing works

Multivariable Modeling of Biomarker Data From the Phase I Foundation for the National Institutes of Health Osteoarthritis Biomarkers Consortium

Hunter, D. J., Deveza, L. A., Collins, J. E., Losina, E., Katz, J. N., Nevitt, M. C., Lynch, J. A., Roemer, F. W., Guermazi, A., Bowes, M. A., et al. (2021) · Arthritis Care & Research · doi:10.1002/acr.24557 · Cited by 59 · see citing works

Pain Trajectories in Knee Osteoarthritis—A Systematic Review and Best Evidence Synthesis on Pain Predictors

Previtali, D., Andriolo, L., Frattura, G. D. L., Boffa, A., Candrian, C., Zaffagnini, S., & Filardo, G. (2020) · Journal of Clinical Medicine · doi:10.3390/jcm9092828 · Cited by 56 · see citing works

Osteoarthritis year in review 2019: imaging

Kijowski, R., Demehri, S., Roemer, F. W., & Guermazi, A. (2019) · Osteoarthritis and Cartilage · doi:10.1016/j.joca.2019.11.009 · Cited by 54 · see citing works

Discovery of an autoantibody signature for the early diagnosis of knee osteoarthritis: data from the Osteoarthritis Initiative

Camacho-Encina, M., Barreiro, V. B., Rego‐Pérez, I., Picchi, F., VanDuin, J., Qiu, J., Fuentes, M., Oreiro, N., LaBaer, J., Ruíz‐Romero, C., et al. (2019) · Annals of the Rheumatic Diseases · doi:10.1136/annrheumdis-2019-215325 · Cited by 46 · see citing works

A Comprehensive Survey on Bone Segmentation Techniques in Knee Osteoarthritis Research: From Conventional Methods to Deep Learning

Ahmed, S. M., & Mstafa, R. J. (2022) · Diagnostics · doi:10.3390/diagnostics12030611 · Cited by 43 · see citing works

DeepKOA: a deep-learning model for predicting progression in knee osteoarthritis using multimodal magnetic resonance images from the osteoarthritis initiative

Hu, J., Zheng, C., Yu, Q., Zhong, L., Yu, K., Chen, Y., Wang, Z., Zhang, B., Dou, Q., & Zhang, X. (2023) · Quantitative Imaging in Medicine and Surgery · doi:10.21037/qims-22-1251 · Cited by 41 · see citing works

AI MSK clinical applications: cartilage and osteoarthritis

Joseph, G. B., McCulloch, C. E., Sohn, J. H., Pedoia, V., Majumdar, S., & Link, T. M. (2021) · Skeletal Radiology · doi:10.1007/s00256-021-03909-2 · Cited by 39 · see citing works

Biodegradable lubricating mesoporous silica nanoparticles for osteoarthritis therapy

Wan, L., Wang, Y., Tan, X., Sun, Y., Luo, J., & Zhang, H. (2020) · Friction · doi:10.1007/s40544-020-0391-2 · Cited by 36 · see citing works

Identification of Risk Factors and Machine Learning-Based Prediction Models for Knee Osteoarthritis Patients

Kokkotis, C., Moustakidis, S., Giakas, G., & Tsaopoulos, D. E. (2020) · Applied Sciences · doi:10.3390/app10196797 · Cited by 36 · see citing works

Trajectories of Structural Disease Progression in Knee Osteoarthritis

Collins, J. E., Neogi, T., & Losina, E. (2020) · Arthritis Care & Research · doi:10.1002/acr.24340 · Cited by 35 · see citing works

Magnetic resonance imaging assessments for knee segmentation and their use in combination with machine/deep learning as predictors of early osteoarthritis diagnosis and prognosis

Martel‐Pelletier, J., Paiement, P., & Pelletier, J. (2023) · Therapeutic Advances in Musculoskeletal Disease · doi:10.1177/1759720x231165560 · Cited by 35 · see citing works

Prediction of knee pain improvement over two years for knee osteoarthritis using a dynamic nomogram based on MRI-derived radiomics: a proof-of-concept study

Lin, T., Peng, S., Lu, S., Fu, S., Zeng, D., Li, J., Chen, T., Fan, T., Lang, C., Feng, S., et al. (2022) · Osteoarthritis and Cartilage · doi:10.1016/j.joca.2022.10.014 · Cited by 33 · see citing works

Prediction of Joint Space Narrowing Progression in Knee Osteoarthritis Patients

Ntakolia, C., Kokkotis, C., Moustakidis, S., & Tsaopoulos, D. E. (2021) · Diagnostics · doi:10.3390/diagnostics11020285 · Cited by 31 · see citing works

Expediting Finite Element Analyses for Subject-Specific Studies of Knee Osteoarthritis: A Literature Review

Paz, A., Orozco, G. A., Korhonen, R. K., García, J. J., & Mononen, M. E. (2021) · Applied Sciences · doi:10.3390/app112311440 · Cited by 30 · see citing works

A comprehensive patient-specific prediction model for temporomandibular joint osteoarthritis progression

Turkestani, N. N. A., Li, T., Bianchi, J., Gurgel, M., Prieto, J. C., Shah, H., Benavides, E., Soki, F. N., Mishina, Y. M., Fontana, M., et al. (2024) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2306132121 · Cited by 29 · see citing works

What Have We Learned From Trajectory Analysis of Clinical Outcomes in Knee and Hip Osteoarthritis Before Surgery?

Wieczorek, M., Rotonda, C., Guillemin, F., & Rat, A. (2019) · Arthritis Care & Research · doi:10.1002/acr.24069 · Cited by 29 · see citing works

Association between current medication use and progression of radiographic knee osteoarthritis: data from the osteoarthritis initiative

Perry, T. A., Wang, X., Nevitt, M. C., Shaheed, C. A., Arden, N., & Hunter, D. J. (2021) · Lara D. Veeken · doi:10.1093/rheumatology/keab059 · Cited by 29 · see citing works

Adversarial Evolving Neural Network for Longitudinal Knee Osteoarthritis Prediction

Hu, K., Wu, W., Li, W., Simić, M., Zomaya, A. Y., & Wang, Z. (2022) · IEEE Transactions on Medical Imaging · doi:10.1109/tmi.2022.3181060 · Cited by 31 · see citing works

Unsupervised machine-learning algorithms for the identification of clinical phenotypes in the osteoarthritis initiative database

Demanse, D., Saxer, F., Lustenberger, P., Tankó, L. B., Nikolaus, P., Rasin, I., Brennan, D. F., Roubenoff, R., Premji, S., Conaghan, P. G., et al. (2022) · Seminars in Arthritis and Rheumatism · doi:10.1016/j.semarthrit.2022.152140 · Cited by 28 · see citing works

Identifying Robust Risk Factors for Knee Osteoarthritis Progression: An Evolutionary Machine Learning Approach

Kokkotis, C., Moustakidis, S., Baltzopoulos, V., Giakas, G., & Tsaopoulos, D. E. (2021) · Healthcare · doi:10.3390/healthcare9030260 · Cited by 27 · see citing works

A pilot study of peripheral blood DNA methylation models as predictors of knee osteoarthritis radiographic progression: data from the Osteoarthritis Initiative (OAI)

Dunn, C. M., Nevitt, M. C., Lynch, J. A., & Jeffries, M. A. (2019) · Scientific Reports · doi:10.1038/s41598-019-53298-9 · Cited by 26 · see citing works

A machine learning pipeline for predicting joint space narrowing in knee osteoarthritis patients

Ntakolia, C., Kokkotis, C., Moustakidis, S., & Tsaopoulos, D. E. (2020) · IEEE International Conference on Bioinformatics and Bioengineering (BIBE) · doi:10.1109/bibe50027.2020.00158 · Cited by 26 · see citing works

A joint multi-modal learning method for early-stage knee osteoarthritis disease classification

Liu, L., Jing, C., Zhang, P., Ma, Q., Zhang, H., Sun, T., & Qiao, H. (2023) · Heliyon · doi:10.1016/j.heliyon.2023.e15461 · Cited by 24 · see citing works

Baseline clinical characteristics of predicted structural and pain progressors in the IMI-APPROACH knee OA cohort

van Helvoort, E. M., Ladel, C. H., Mastbergen, S. C., Kloppenburg, M., Blanco, F. J., Haugen, I. K., Berenbaum, F., Bacardit, J., Widera, P., Welsing, P. M. J., et al. (2021) · RMD Open · doi:10.1136/rmdopen-2021-001759 · Cited by 22 · see citing works

Gait Alterations and Association With Worsening Knee Pain and Physical Function: A Machine Learning Approach With Wearable Sensors in the Multicenter Osteoarthritis Study

Bacon, K. L., Felson, D. T., Jafarzadeh, S. R., Kolachalama, V. B., Hausdorff, J. M., Gazit, E., Stefanik, J. J., Corrigan, P., Segal, N. A., Lewis, C. E., et al. (2024) · Arthritis Care & Research · doi:10.1002/acr.25327 · Cited by 21 · see citing works

Defining and predicting radiographic knee osteoarthritis progression: a systematic review of findings from the osteoarthritis initiative

Joo, P. Y., Borjali, A., Chen, A. F., Muratoglu, O. K., & Varadarajan, K. M. (2022) · Knee Surgery Sports Traumatology Arthroscopy · doi:10.1007/s00167-021-06768-5 · Cited by 21 · see citing works

Prediction Models for Knee Osteoarthritis: Review of Current Models and Future Directions.

Ramazanian, T., Fu, S., Sohn, S., Taunton, M. J., & Kremers, H. M. (2023) · PubMed Central · doi:10.22038/abjs.2022.58485.2897 · Cited by 21 · see citing works

Prediction Models to Estimate the Future Risk of Osteoarthritis in the General Population: A Systematic Review

Appleyard, T., Thomas, M. J., Antcliff, D., & Peat, G. (2022) · Arthritis Care & Research · doi:10.1002/acr.25035 · Cited by 20 · see citing works

Identification of most important features based on a fuzzy ensemble technique: Evaluation on joint space narrowing progression in knee osteoarthritis patients

Ntakolia, C., Kokkotis, C., Moustakidis, S., & Tsaopoulos, D. E. (2021) · International Journal of Medical Informatics · doi:10.1016/j.ijmedinf.2021.104614 · Cited by 19 · see citing works

Integration of Swin UNETR and statistical shape modeling for a semi-automated segmentation of the knee and biomechanical modeling of articular cartilage

Kakavand, R., Palizi, M., Tahghighi, P., Ahmadi, R. H., Gianchandani, N., Adeeb, S., de Souza, R. M., Edwards, W. B., & Komeili, A. (2024) · Scientific Reports · doi:10.1038/s41598-024-52548-9 · Cited by 18 · see citing works

End-to-End Prediction of Knee Osteoarthritis Progression With Multimodal Transformers

Panfilov, E., Saarakkala, S. S., Nieminen, M. T., & Tiulpin, A. (2025) · IEEE Journal of Biomedical and Health Informatics · doi:10.1109/jbhi.2025.3536170 · Cited by 17 · see citing works

Machine learning models for clinical and structural knee osteoarthritis prediction: Recent advancements and future directions

Joseph, G. B., McCulloch, C. E., Nevitt, M. C., Lane, N. E., Majumdar, S., & Link, T. M. (2025) · Osteoarthritis and Cartilage Open · doi:10.1016/j.ocarto.2025.100654 · Cited by 17 · see citing works

Prediction of pain in knee osteoarthritis patients using machine learning: Data from Osteoarthritis Initiative

Alexos, A., Kokkotis, C., Moustakidis, S., Papageorgiou, E. I., & Tsaopoulos, D. E. (2020) · International Conference on Information, Intelligence, Systems & Applications (IISA) · doi:10.1109/iisa50023.2020.9284379 · Cited by 17 · see citing works

Radiographic Biomarkers for Knee Osteoarthritis: A Narrative Review

Almhdie-Imjabbar, A., Toumi, H., & Lespessailles, É. (2023) · Life · doi:10.3390/life13010237 · Cited by 14 · see citing works

An ensemble clinical and MR-image deep learning model predicts 8-year knee pain trajectory: Data from the osteoarthritis initiative

Lee, J. J., Liu, F., Majumdar, S., & Pedoia, V. (2021) · Osteoarthritis Imaging · doi:10.1016/j.ostima.2021.100003 · Cited by 13 · see citing works

Next-generation osteoarthritis models: integrating biological, computational, and engineering approaches

Labusca, L. S. (2025) · Stem Cell Research & Therapy · doi:10.1186/s13287-025-04790-9 · Cited by 12 · see citing works

Optimizing CNN-Based Diagnosis of Knee Osteoarthritis: Enhancing Model Accuracy with CleanLab Relabeling

Momenpour, T., & Mallouh, A. A. (2025) · Diagnostics · doi:10.3390/diagnostics15111332 · Cited by 12 · see citing works

Prediction of progression rate and fate of osteoarthritis: Comparison of machine learning algorithms

Yoo, H. J., Jeong, H. W., Kim, S. W., Kim, M., Lee, J. I., & Lee, Y. S. (2022) · Journal of Orthopaedic Research® · doi:10.1002/jor.25398 · Cited by 12 · see citing works

Biomarker-Guided Imaging and AI-Augmented Diagnosis of Degenerative Joint Disease

Kumar, R., Sporn, K., Borole, A., Khanna, A., Gowda, C., Paladugu, P., Ngo, A., Jagadeesan, R., Zaman, N., & Tavakkoli, A. (2025) · Diagnostics · doi:10.3390/diagnostics15111418 · Cited by 10 · see citing works

Automated machine learning-based prediction of the progression of knee pain, functional decline, and incidence of knee osteoarthritis in individuals at high risk of knee osteoarthritis: Data from the osteoarthritis initiative study

Chen, T., & Or, C. K. (2023) · Digital Health · doi:10.1177/20552076231216419 · Cited by 8 · see citing works

Identifying the Phenotypic and Temporal Heterogeneity of Knee Osteoarthritis: Data From the Osteoarthritis Initiative

Li, M., Lan, L., Luo, J.-W., Peng, L., Li, X., & Zhou, X.-B. (2021) · Frontiers in Public Health · doi:10.3389/fpubh.2021.726140 · Cited by 8 · see citing works

Risk factors associated with the occurrence of total knee arthroplasty in patients with knee osteoarthritis: a nested case–control study

Pelletier, J., Dorais, M., Paiement, P., Raynauld, J., & Martel‐Pelletier, J. (2022) · Therapeutic Advances in Musculoskeletal Disease · doi:10.1177/1759720x221091359 · Cited by 6 · see citing works

Bayesian Graphical Models for Multiscale Inference in Medical Image-Based Joint Degeneration Analysis

Kumar, R., Marla, K., Ravi, P., Sporn, K., Srinivas, R., Vaja, S., Ngo, A., & Tavakkoli, A. (2025) · Diagnostics · doi:10.3390/diagnostics15182295 · Cited by 5 · see citing works

Development and evaluation of nomograms for predicting osteoarthritis progression based on MRI cartilage parameters: data from the FNIH OA biomarkers Consortium

Deng, C., Sun, Y., Zhang, Z., Ma, X., Liu, X., & Zhou, F. (2023) · BMC Medical Imaging · doi:10.1186/s12880-023-01001-w · Cited by 5 · see citing works

Patient and Surgical Factors Associated With Long-Term Mortality Outcomes Up to Fifteen Years After Total Hip and Knee Arthroplasty: An Australian Orthopaedic Association National Joint Replacement Registry Study

Zhou, Y., Fraval, A., Vertullo, C. J., Du, P., Babazadeh, S., & Stevens, J. M. (2024) · The Journal of Arthroplasty · doi:10.1016/j.arth.2024.11.012 · Cited by 4 · see citing works

Swin UNETR Segmentation with Automated Geometry Filtering for Biomechanical Modeling of Knee Joint Cartilage

Kakavand, R., Tahghighi, P., Ahmadi, R. H., Edwards, W. B., & Komeili, A. (2025) · Annals of Biomedical Engineering · doi:10.1007/s10439-024-03675-x · Cited by 4 · see citing works

Early Diagnosis of Knee Osteoarthritis With a Natural Language Processing–Driven Approach Based on Clinician Notes: Development and Validation Study

Thanyakunsajja, N., Jitkajornwanich, K., Xu, S., Shin, D., & Charoenporn, P. (2025) · JMIR Formative Research · doi:10.2196/64536 · Cited by 4 · see citing works

A clinical application of gait quality patterns in osteoarthritis

Mejia, A. C., Gulde, P., & Salinas, C. G. (2024) · Gait & Posture · doi:10.1016/j.gaitpost.2024.10.011 · Cited by 4 · see citing works

Comprehensive comparative analysis of infrapatellar fat pad morphologies in a longitudinal knee osteoarthritis exploratory study: new insights into its role as an independent prognostic marker

Pelletier, J., Paiement, P., Abram, F., Dorais, M., Raynauld, J., & Martel‐Pelletier, J. (2025) · Arthritis Research & Therapy · doi:10.1186/s13075-025-03513-y · Cited by 4 · see citing works

Prediction of overall survival in patients with Stage I esophageal cancer: A novel web‐based calculator

Yang, Z., Yang, F., Yang, M., Qi, Y., Jiang, M., Xuan, J., Liu, Y., Tao, H., Liu, Y., & Wang, F. (2021) · Journal of Surgical Oncology · doi:10.1002/jso.26594 · Cited by 4 · see citing works

Multi-resolution Networks For Flexible Irregular Time Series Modeling (Multi-FIT)Preprint

Singh, B. P., Deznabi, I., Narasimhan, B., Kucharski, B., Uppaal, R., Josyula, A., & Fiterau, M. (2019) · arXiv (Cornell University) · doi:10.48550/arxiv.1905.00125 · Cited by 4 · see citing works

Determining individual trajectories of joint space loss: improved statistical methods for monitoring knee osteoarthritis disease progression

Parsons, C. M., Judge, A., Meyer, R., Bruyère, O., Petit-Dop, F., Chapurlat, R. D., Reginster, J.-Y., Cooper, C. C., & Inskip, H. M. (2020) · Osteoarthritis and Cartilage · doi:10.1016/j.joca.2020.09.009 · Cited by 3 · see citing works

Optimal knee osteoarthritis diagnosis using hybrid deep belief network based on Salp swarm optimization method

Balasubramanian, K., Kishore, R., & Krishnamoorthy, G. D. (2022) · Concurrency and Computation Practice and Experience · doi:10.1002/cpe.6913 · Cited by 3 · see citing works

Endoscopic Surgical Treatment of Osteoarthritis and Prognostic Model Construction

Su, Q., & Xu, G. (2022) · Computational and Mathematical Methods in Medicine · doi:10.1155/2022/1799177 · Cited by 3 · see citing works

A Novel Approach Based on Hypergraph Convolutional Neural Networks for Cartilage Shape Description and Longitudinal Prediction of Knee Osteoarthritis Progression

Theocharis, J. B., Chadoulos, C. G., & Symeonidis, A. L. (2025) · Machine Learning and Knowledge Extraction · doi:10.3390/make7020040 · Cited by 3 · see citing works

The role of mathematical models in prediction of osteoarthritis development

Pawlikowski, M., Sikora, S., & Ostrowski, G. (2025) · Computers in Biology and Medicine · doi:10.1016/j.compbiomed.2025.110407 · Cited by 3 · see citing works

Artificial Intelligence and Machine Learning for Osteoarthritis and Cartilage Assessment

Jo, S. Y., & Sebro, R. (2025) · Radiologic Clinics of North America · doi:10.1016/j.rcl.2025.09.001 · Cited by 2 · see citing works

Beyond the algorithms: Challenges in predicting knee osteoarthritis pain from a machine learning point of view

Bayramoğlu, N., Englund, M., Haugen, I. K., Ishijima, M., & Saarakkala, S. S. (2025) · Osteoarthritis Imaging · doi:10.1016/j.ostima.2025.100381 · Cited by 2 · see citing works

Association of Wearable Sensor–Derived Gait Measures With Cartilage Damage Over Two Years Among Adults With or at Risk of Knee Osteoarthritis

Bacon, K. L., Felson, D. T., Jafarzadeh, S. R., Hausdorff, J. M., Gazit, E., Guermazi, A., Roemer, F. W., Segal, N. A., Lewis, C. E., Nevitt, M. C., et al. (2026) · Arthritis Care & Research · doi:10.1002/acr.80018 · Cited by 2 · see citing works

Radiographic imaging-based joint degradation detection using deep learning

(2023) · International Journal of Advanced Technology and Engineering Exploration · doi:10.19101/ijatee.2023.10101973 · Cited by 2 · see citing works

Forecasting in multivariate irregularly sampled time series with missing valuesPreprint

Srivastava, S., Sen, P., & Reinwald, B. (2020) · arXiv (Cornell University) · doi:10.48550/arxiv.2004.03398 · Cited by 2 · see citing works

An Integrated Multi-modal Learning Method for Early-stage Knee Osteoarthritis Disease ClassificationPreprint

Liu, L., Jing, C., & Ma, Q. (2022) · Research Square · doi:10.21203/rs.3.rs-2329021/v1 · Cited by 2 · see citing works

Microbiome-Augmented Model for Predicting Knee Osteoarthritis Progression Based on Gut Microbiota and Kellgren-Lawrence Classification

Jiang, L., Liu, S., & Kong, H. (2024) · Cureus · doi:10.7759/cureus.73402 · Cited by 1 · see citing works

Association of baseline MRI-defined structural features with knee symptom trajectories over nine years: Data from the osteoarthritis initiative (OAI)

Liu, S., Sun, X., Ge, Y., Duong, T. N., & Kwoh, C. K. (2025) · Osteoarthritis Imaging · doi:10.1016/j.ostima.2025.100380 · Cited by 1 · see citing works

Risk factors for diagnosis of Escherichia coli infection after flexible ureteroscope holmium laser lithotripsy by imaging information technology under Nomogram mathematical model

Zhang, Y., Zhang, Q., Lv, J., Zhang, D., Kaddouri, M., & Dulaimi, S. H. K. A. (2021) · Results in Physics · doi:10.1016/j.rinp.2021.104330 · Cited by 1 · see citing works

Patient-specific modeling of pain progression: a use case on knee osteoarthritis patients using machine learning algorithms

Moustakidis, S., Kokkotis, C., & Tsaopoulos, D. E. (2023) · Elsevier eBooks · doi:10.1016/b978-0-12-823913-1.00032-4 · Cited by 1 · see citing works

Machine Learning Models for Prediction of Progression of Knee Osteoarthritis: A Comprehensive Analysis

Miraj, M. (2024) · Journal of Pharmacy And Bioallied Sciences · doi:10.4103/jpbs.jpbs_1000_23 · Cited by 1 · see citing works

Knee Osteoarthritis Prediction using Transfer Learning

Rawat, A., Dhyani, A., Panwa, D., Bisht, G., Vats, S., & Sharma, V. (2024) · IEEE World Conference on Applied Intelligence and Computing (AIC) · doi:10.1109/aic61668.2024.10731036 · Cited by 1 · see citing works

How to Make a Strategy for Knee Arthritis Treatment

Seo, S.-S., & Roh, S.-M. (2021) · Springer eBooks · doi:10.1007/978-981-16-4217-3_15 · Cited by 1 · see citing works

FLARe: Forecasting by Learning Anticipated RepresentationsPreprint

Devarakonda, S. T., Wu, J. Y., Fung, Y. R., & Fiterau, M. (2019) · arXiv (Cornell University) · doi:10.48550/arxiv.1904.08930 · Cited by 1 · see citing works

A Deep Learning Method for Identifying Predictors of Knee Osteoarthritis Radiographic Progression From Baseline MRIPreprint

Schiratti, J.-B., Dubois, R., Hérent, P., Cahané, D., Dachary, J., Clozel, T., Wainrib, G., Keime-Guibert, F., Lalande, A., Pueyo, M. E., et al. (2021) · Research Square · doi:10.21203/rs.3.rs-521841/v1 · Cited by 1 · see citing works

Charting Aging Trajectories of Knee Cartilage Thickness for Early Osteoarthritis Risk Prediction: An MRI Study from the Osteoarthritis Initiative CohortPreprint

Li, T., Luo, T., Chen, B., Huang, C., Shen, Z., Xu, Z., Nissman, D., Golightly, Y. M., Nelson, A. E., Niethammer, M., et al. (2023) · medRxiv · doi:10.1101/2023.09.12.23295398 · Cited by 2 · see citing works

Osteoarthritis: Towards a progressive APPROACH

van Helvoort, E. M. (2022) · doi:10.33540/1227

A Machine Learning based Approach for Detection of Osteoarthritis using Thermal Images

Afroze, A. S., Selvi, R. T., Beham, M. P., Judith, J., & Lakshmi, S. S. P. (2023) · Journal of Innovative Image Processing · doi:10.36548/jiip.2023.2.004

Infectious Disease

Rothschild, B. M., Surmik, D., & Bertozzo, F. (2023) · Springer eBooks · doi:10.1007/978-3-031-28624-7_9

SSANet: Side-by-Side Additive Network for Knee Osteoarthritis Severity Detection from X-Ray Images

Tewari, R., Bhattacharjee, D., Roy, H., & Krejcar, O. (2024) · Lecture notes in networks and systems · doi:10.1007/978-981-97-2611-0_24

Identity-Consistent Diffusion Network for Grading Knee Osteoarthritis Progression in Radiographic Imaging

Wu, W., Hu, K., Yue, W., Li, W., Simić, M., Li, C., Xiang, W., & Wang, Z. (2024) · Lecture notes in computer science · doi:10.1007/978-3-031-72907-2_18

Structural and Statistical Texture Approaches in the Radiological Assessment of Knee Osteoarthritis: A Multimodal ReviewPreprint

More, S., Narang, G., Bhosale, A., & Maske, R. (2025) · Research Square · doi:10.21203/rs.3.rs-7239085/v1

A Dynamic Hypergraph-Based Encoder–Decoder Risk Model for Longitudinal Predictions of Knee Osteoarthritis Progression

Theocharis, J. B., Chadoulos, C. G., & Symeonidis, A. L. (2025) · Machine Learning and Knowledge Extraction · doi:10.3390/make7030094

Additional file 1 of A deep learning method for predicting knee osteoarthritis radiographic progression from MRI

Schiratti, J.-B., Dubois, R., Hérent, P., Cahané, D., Dachary, J., Clozel, T., Wainrib, G., Keime-Guibert, F., Lalande, A., Pueyo, M. E., et al. (2021) · Figshare · doi:10.6084/m9.figshare.16829146

Temporal Patterns of Wearable Accelerometer-Measured Physical Activity and Symptom Worsening in Knee Osteoarthritis: A 2-Year Longitudinal Study from the Osteoarthritis Initiative

Kushioka, J., Sun, R., & Smuck, M. W. (2026) · Sensors · doi:10.3390/s26030982

Facteurs pronostiques de l’évolution de la santé perçue dans l’arthrose symptomatique de hanche et de genou : analyses de la cohorte KHOALA

Wieczorek, M. (2019) · doi:10.70675/79bef0c4z4064z4662z930az178df2db0889

Accurate classification and prediction of knee osteoarthritis based on Al-Biruni Earth Radius metaheuristic optimizer and LSTM classifier

Diab, A. G., El‐kenawy, E. M., Areed, N. F. F., Amer, H. M., & El-Seddek, M. (2026) · Scientific Reports · doi:10.1038/s41598-026-46131-7

Profiling of knee osteoarthritis patients and progression to total knee arthroplasty based on symptom trajectories: evidence on more than 6000 knees from the Osteoarthritis Initiative

Bensa, A., Prevot, L. B., Pignotti, E., Candrian, C., & Filardo, G. (2026) · Journal of Cartilage & Joint Preservation · doi:10.1016/j.jcjp.2026.100312

Impact of microstructural alterations to collagen networks on their mechanical behavior: a fiber in silico study of the articular cartilage surface

Núñez-Ortega, E., Sanz‐Herrera, J. A., Gaffney, E. A., Brown, C. P., & Reina-Romo, E. (2026) · International Journal of Engineering Science · doi:10.1016/j.ijengsci.2026.104606

Risk stratification for the rapid pain progression phenotype in knee osteoarthritis using interpretable multimodal machine learning: Development in the Osteoarthritis Initiative and external evaluation in the Prospective Cohort of Osteoarthritis from A CoruñaPreprint

Blanco, F. J., Martínez-Sotodosos, L., Oreiro, N., Galindo, L., Vázquez-García, J., Noriega-Cobo, D. M., Lourido, L., Paz-González, R., Quaranta, P., Calamia, V., et al. (2026) · medRxiv · doi:10.64898/2026.07.21.26357764

Diagnostic model based on CT and plantar pressure features for moderate-to-severe knee osteoarthritisPreprint

Wang, J., Xu, L., Dong, S., Liu, Z., Qu, J., Tang, H., Wang, Y., & Jiang, J. (2026) · Research Square · doi:10.21203/rs.3.rs-10509154/v1

A review on predictive modeling studies on women's health and nutrition

Paul, S., & Parija, T. (2026) · Elsevier eBooks · doi:10.1016/b978-0-443-23671-6.00010-4

Predictive models of radiographic progression and pain progression in patients with knee osteoarthritis: data from the FNIH OA biomarkers consortium project

Li, X., Li, C., & Zhang, P. (2024) · Arthritis Research & Therapy · doi:10.1186/s13075-024-03346-1 · Cited by 7 · see citing works

A machine learning-based predictive model for progression of knee osteoarthritis from clinical data

Li, H. H. T., Chan, L.-C., & Wen, C. (2020) · Osteoarthritis and Cartilage · doi:10.1016/j.joca.2020.02.485

Predicting OA progression: results from the Vancouver knee osteoarthritis progression study

Cibere, J., Sayre, E. C., Guermazi, A., Nicolaou, S., Esdaile, J. M., Kopec, J. A., Singer, J., Thorne, A., & Wong, H. (2012) · Osteoarthritis and Cartilage · doi:10.1016/j.joca.2012.02.288

Development of the machine learning model that is highly validated and easily applicable to predict radiographic knee osteoarthritis progression

Lee, D. W., Han, H., Ro, D. H., & Lee, Y. S. (2024) · Journal of Orthopaedic Research® · doi:10.1002/jor.25982 · Cited by 6 · see citing works

A clinical model to predict the progression of knee osteoarthritis: data from Dryad

Shen, L., & Yue, S. (2023) · Journal of Orthopaedic Surgery and Research · doi:10.1186/s13018-023-04118-4 · Cited by 13 · see citing works