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For: Navarini L, Caso F, Costa L, Currado D, Stola L, Perrotta F, Delfino L, Sperti M, Deriu MA, Ruscitti P, Pavlych V, Corrado A, Di Benedetto G, Tasso M, Ciccozzi M, Laudisio A, Lunardi C, Cantatore FP, Lubrano E, Giacomelli R, Scarpa R, Afeltra A. Cardiovascular Risk Prediction in Ankylosing Spondylitis: From Traditional Scores to Machine Learning Assessment. Rheumatol Ther 2020;7:867-82. [PMID: 32939675 DOI: 10.1007/s40744-020-00233-4] [Cited by in Crossref: 2] [Cited by in F6Publishing: 2] [Article Influence: 1.0] [Reference Citation Analysis]
Number Citing Articles
1 Muhammed H, Misra DP, Jain N, Ganguly S, Pattanaik SS, Rai MK, Anuja AK, Mohindra N, Kumar S, Agarwal V. The comparison of cardiovascular disease risk prediction scores and evaluation of subclinical atherosclerosis in rheumatoid arthritis: a cross-sectional study. Clin Rheumatol 2022. [PMID: 36006556 DOI: 10.1007/s10067-022-06349-y] [Reference Citation Analysis]
2 Navarini L, Currado D, Marino A, Di Donato S, Biaggi A, Caso F, Costa L, Tasso M, Ruscitti P, Pavlych V, Berardicurti O, Ciancio A, Pantano I, Camarda F, Chimenti MS, D'Antonio A, Ursini F, Corrado A, Cantatore FP, Perricone R, Guggino G, Ciccia F, Cipriani P, Scarpa R, Afeltra A, Giacomelli R. Persistence of C-reactive protein increased levels and high disease activity are predictors of cardiovascular disease in patients with axial spondyloarthritis. Sci Rep 2022;12:7498. [PMID: 35525861 DOI: 10.1038/s41598-022-11640-8] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]
3 Perrotta FM, Scriffignano S, Ciccia F, Lubrano E. Therapeutic Targets for Ankylosing Spondylitis - Recent Insights and Future Prospects. Open Access Rheumatol 2022;14:57-66. [PMID: 35469137 DOI: 10.2147/OARRR.S295033] [Cited by in Crossref: 2] [Cited by in F6Publishing: 1] [Article Influence: 2.0] [Reference Citation Analysis]
4 Sperti M, Malavolta M, Staunovo Polacco F, Dellavalle A, Ruggieri R, Bergia S, Fazio A, Santoro C, Deriu MA. Cardiovascular risk prediction: from classical statistical methods to machine learning approaches. Minerva Cardiol Angiol 2022;70:102-22. [PMID: 35261223 DOI: 10.23736/S2724-5683.21.05868-3] [Reference Citation Analysis]
5 Nona P, Russell C. Cardio-Rheumatology. Medical Clinics of North America 2022;106:349-63. [DOI: 10.1016/j.mcna.2021.11.010] [Cited by in Crossref: 2] [Cited by in F6Publishing: 2] [Article Influence: 2.0] [Reference Citation Analysis]
6 Roberts MJ, Leonard AN, Bishop NC, Moorthy A. Lifestyle modification and inflammation in people with axial spondyloarthropathy-A scoping review. Musculoskeletal Care 2022. [PMID: 35179819 DOI: 10.1002/msc.1625] [Reference Citation Analysis]
7 Faramand Z, Alrawashdeh M, Helman S, Bouzid Z, Martin-Gill C, Callaway C, Al-Zaiti S. Your neighborhood matters: A machine-learning approach to the geospatial and social determinants of health in 9-1-1 activated chest pain. Res Nurs Health 2021. [PMID: 34820853 DOI: 10.1002/nur.22199] [Reference Citation Analysis]
8 Kingsmore KM, Puglisi CE, Grammer AC, Lipsky PE. An introduction to machine learning and analysis of its use in rheumatic diseases. Nat Rev Rheumatol 2021;17:710-30. [PMID: 34728818 DOI: 10.1038/s41584-021-00708-w] [Cited by in F6Publishing: 7] [Reference Citation Analysis]
9 Ferraz-Amaro I, Rueda-Gotor J, Genre F, Corrales A, Blanco R, Portilla V, González Mazón I, Llorca J, Expósito R, Vicente EF, Quevedo-Abeledo JC, Rodríguez-Lozano C, Ortega-Castro R, Ladehesa-Pineda ML, Fernández-Carballido C, Martínez-Vidal MP, Castro-Corredor D, Anino-Fernández J, García Vivar ML, Galíndez-Agirregoikoa E, Peiteado D, Plasencia-Rodríguez C, Montes Perez E, Fernández Díaz C, Castañeda S, González-Gay MÁ. Potential relation of cardiovascular risk factors to disease activity in patients with axial spondyloarthritis. Ther Adv Musculoskelet Dis 2021;13:1759720X211033755. [PMID: 34377161 DOI: 10.1177/1759720X211033755] [Reference Citation Analysis]
10 Ionescu M, Ionescu P, Suceveanu AP, Stoian AP, Motofei I, Ardeleanu V, Parepa IR. Cardiovascular risk estimation in young patients with ankylosing spondylitis: A new model based on a prospective study in Constanta County, Romania. Exp Ther Med 2021;21:529. [PMID: 33815602 DOI: 10.3892/etm.2021.9961] [Cited by in Crossref: 1] [Cited by in F6Publishing: 3] [Article Influence: 1.0] [Reference Citation Analysis]