Study on Rheumatoid Arthritis Prediction Model With Machine Learning and Ensemble Learning Methods, and Demographic, Clinical, Laboratory Characteristics of These Patients

Kemal Üreten; Yüksel Maraş; Ebru Atalar; Kevser Orhan

doi:10.29130/dubited.1768590

EN TR

Study on Rheumatoid Arthritis Prediction Model With Machine Learning and Ensemble Learning Methods, and Demographic, Clinical, Laboratory Characteristics of These Patients

Abstract

The aim of this study is to develop a diagnostic and predictive model for rheumatoid arthritis (RA) with machine learning and ensemble learning methods using data from patients who applied to the rheumatology outpatient clinic with complaints of pain in the hand joints and to review the demographic, clinical and laboratory results of these RA patients. This study was conducted on demographic properties, clinical findings, and laboratory test results of a total of 421 patients, 260 with RA and 161 non-RA. Machine learning and ensemble learning algorithms were used for prediction. In this study, ensemble learning algorithms showed better performance than machine learning algorithms. With the Random Forest Classifier model 88% accuracy (95% confidence interval (CI), 81% - 94% ), 94% sensitivity (95% CI, 88% - 99%), 78% specificity (95% CI, 69% - 86%), 87% positive predictive value (PPV) (95% CI, 79% - 94%), 90% F1 score (95% CI, 84% - 96%), and 0.92 AUC (area under the curve) results were obtained. All three developed ensemble learning models showed similar performance in statistical metrics. These developed models can be improved with new multicenter studies with more patients and can be used in daily practice.

Keywords

Rheumatoid arthritis, Machine learning, Ensemble learning, Logistic regression, Support vector machines

Supporting Institution

This research received no external funding.

Project Number

None

Ethical Statement

An ethical approval certificate was obtained from the local ethic commitee, Ankara Bilkent City Hospital, Clinical Research Ethics Committee No. 1, date : 16.08.2023, no : E1-23-3650. This study is a retrospective study and ethics committee approval was obtained.

Thanks

The authors do not wish to acknowledge any individual or institution.

Makine Öğrenmesi ve Topluluk Öğrenme Yöntemleriyle Romatoid Artrit Tahmin Modeli Üzerinde Çalışma ve Bu Hastaların Demografik, Klinik ve Laboratuvar Özellikleri

Abstract

Bu çalışmanın amacı, el eklemlerinde ağrı şikayetiyle romatoloji polikliniğine başvuran hastalardan alınan veriler kullanılarak, makine öğrenmesi ve topluluk öğrenmesi yöntemleriyle romatoid artrit (RA) için tanı ve tahmin modeli geliştirmek ve bu RA hastalarının demografik, klinik ve laboratuvar sonuçlarını incelemektir. Bu çalışma, 260 RA'lı ve 161 RA olmayan olmak üzere toplam 421 hastanın demografik özellikleri, klinik bulguları ve laboratuvar test sonuçları üzerinde yürütülmüştür. Tahmin için makine öğrenmesi ve topluluk öğrenme algoritmaları kullanılmıştır. Bu çalışmada, topluluk öğrenme algoritmaları, makine öğrenmesi algoritmalarına göre daha iyi performans göstermiştir. Yığınlama modeli ile %92 doğruluk (%95 güven aralığı (GA), %89-%95), %94 duyarlılık (%95 GA, %91-%97), %88 özgüllük (%95 GA, %84-%91), %92 pozitif tahmin değeri (PPV) (%95 GA, %89-%95), %91 F1 skoru (%95 GA, %88-%94) ve 0,95 AUC (eğri altında kalan alan) sonuçları elde edilmiştir. En iyi performans, yığınlama topluluk öğrenme modeli ile elde edilmiştir. Önerilen bu model, daha fazla hasta içeren yeni çok merkezli çalışmalarla geliştirilebilir, böylece geliştirilen model günlük pratikte kullanılabilir.

Keywords

Romatoid artrit, Makine öğrenmesi, Topluluk öğrenmesi, Lojistik regresyon, Destek vektör makineleri

Project Number

None

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Details

Primary Language

English

Subjects

Machine Learning Algorithms, Classification Algorithms

Journal Section

Research Article

Authors

Kemal Üreten ^*
0000-0002-7673-4399
Türkiye

Yüksel Maraş
0000-0001-9319-0955
Türkiye

Ebru Atalar
0000-0003-2708-0373
Türkiye

Kevser Orhan
0000-0001-8639-751X
Türkiye

Publication Date

July 24, 2026

Submission Date

August 19, 2025

Acceptance Date

March 29, 2026

Published in Issue

Year 2026 Volume: 14 Number: 3

DOI

https://doi.org/10.29130/dubited.1768590

IZ

https://izlik.org/JA85UW89NW

APA

Üreten, K., Maraş, Y., Atalar, E., & Orhan, K. (2026). Study on Rheumatoid Arthritis Prediction Model With Machine Learning and Ensemble Learning Methods, and Demographic, Clinical, Laboratory Characteristics of These Patients. Duzce University Journal of Science and Technology, 14(3), 695-704. https://doi.org/10.29130/dubited.1768590

AMA

1.Üreten K, Maraş Y, Atalar E, Orhan K. Study on Rheumatoid Arthritis Prediction Model With Machine Learning and Ensemble Learning Methods, and Demographic, Clinical, Laboratory Characteristics of These Patients. DUBİTED. 2026;14(3):695-704. doi:10.29130/dubited.1768590

Chicago

Üreten, Kemal, Yüksel Maraş, Ebru Atalar, and Kevser Orhan. 2026. “Study on Rheumatoid Arthritis Prediction Model With Machine Learning and Ensemble Learning Methods, and Demographic, Clinical, Laboratory Characteristics of These Patients”. Duzce University Journal of Science and Technology 14 (3): 695-704. https://doi.org/10.29130/dubited.1768590.

EndNote

Üreten K, Maraş Y, Atalar E, Orhan K (July 1, 2026) Study on Rheumatoid Arthritis Prediction Model With Machine Learning and Ensemble Learning Methods, and Demographic, Clinical, Laboratory Characteristics of These Patients. Duzce University Journal of Science and Technology 14 3 695–704.

IEEE

[1]K. Üreten, Y. Maraş, E. Atalar, and K. Orhan, “Study on Rheumatoid Arthritis Prediction Model With Machine Learning and Ensemble Learning Methods, and Demographic, Clinical, Laboratory Characteristics of These Patients”, DUBİTED, vol. 14, no. 3, pp. 695–704, July 2026, doi: 10.29130/dubited.1768590.

ISNAD

Üreten, Kemal - Maraş, Yüksel - Atalar, Ebru - Orhan, Kevser. “Study on Rheumatoid Arthritis Prediction Model With Machine Learning and Ensemble Learning Methods, and Demographic, Clinical, Laboratory Characteristics of These Patients”. Duzce University Journal of Science and Technology 14/3 (July 1, 2026): 695-704. https://doi.org/10.29130/dubited.1768590.

JAMA

1.Üreten K, Maraş Y, Atalar E, Orhan K. Study on Rheumatoid Arthritis Prediction Model With Machine Learning and Ensemble Learning Methods, and Demographic, Clinical, Laboratory Characteristics of These Patients. DUBİTED. 2026;14:695–704.

MLA

Üreten, Kemal, et al. “Study on Rheumatoid Arthritis Prediction Model With Machine Learning and Ensemble Learning Methods, and Demographic, Clinical, Laboratory Characteristics of These Patients”. Duzce University Journal of Science and Technology, vol. 14, no. 3, July 2026, pp. 695-04, doi:10.29130/dubited.1768590.

Vancouver

1.Kemal Üreten, Yüksel Maraş, Ebru Atalar, Kevser Orhan. Study on Rheumatoid Arthritis Prediction Model With Machine Learning and Ensemble Learning Methods, and Demographic, Clinical, Laboratory Characteristics of These Patients. DUBİTED. 2026 Jul. 1;14(3):695-704. doi:10.29130/dubited.1768590

Study on Rheumatoid Arthritis Prediction Model With Machine Learning and Ensemble Learning Methods, and Demographic, Clinical, Laboratory Characteristics of These Patients

Abstract

Keywords

Supporting Institution

Project Number

Ethical Statement

Thanks

Makine Öğrenmesi ve Topluluk Öğrenme Yöntemleriyle Romatoid Artrit Tahmin Modeli Üzerinde Çalışma ve Bu Hastaların Demografik, Klinik ve Laboratuvar Özellikleri

Abstract

Keywords

Project Number

References

Details

Primary Language

Subjects

Journal Section

Authors

Publication Date

Submission Date

Acceptance Date

Published in Issue

DOI

IZ

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