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Machine LearningDeep Learning in Rheumatological Screening A Systematic Review

Cilt: 16 Sayı: 3 31 Aralık 2023
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Machine LearningDeep Learning in Rheumatological Screening A Systematic Review

Öz

Machine learning and deep learning techniques have been used in many fields, especially automatic image processing techniques, in recent years. In light of these developments, it has become inevitable to develop applications in the medical field. This study focuses on the past few years of research using machine learning and deep learning methods in the context of image processing in the field of rheumatology. This review provides researchers with the latest information on the use of deep learning and machine learning and inspires them to generate new ideas in their research by analyzing image processing systems performed by these artificial intelligence methods. In the proposed systematic review, 28 articles covering the application of deep learning and machine learning methods in the domain of rheumatology with the aim of digital image processing in the last 18 years were evaluated. Experiments emphasize that machine learning and deep learning methods provide significant segmentation accuracy and better case classification accuracy for various rheumatologic diseases like rheumatoid arthritis, osteoarthritis, and ankylosing spondylitis. Lastly submitted review presents possible different research ideas for related researchers to concentrate on for their future studies.

Anahtar Kelimeler

Kaynakça

  1. Aizenberg, E., Roex, E. A., Nieuwenhuis, W. P., Mangnus, L., van der Helm‐van Mil, A. H., Reijnierse, M., . . . Stoel, B. C. (2018). Automatic quantification of bone marrow edema on MRI of the wrist in patients with early arthritis: a feasibility study. Magnetic resonance in medicine, 79(2), 1127-1134.
  2. Algan, G., & Ulusoy, I. (2021). Image classification with deep learning in the presence of noisy labels: A survey. Knowledge-Based Systems, 215, 106771.
  3. Antony, J., McGuinness, K., O'Connor, N. E., & Moran, K. (2016). Quantifying radiographic knee osteoarthritis severity using deep convolutional neural networks. Paper presented at the 2016 23rd International Conference on Pattern Recognition (ICPR).
  4. Ashinsky, B. G., Bouhrara, M., Coletta, C. E., Lehallier, B., Urish, K. L., Lin, P. C., . . . Spencer, R. G. (2017). Predicting early symptomatic osteoarthritis in the human knee using machine learning classification of magnetic resonance images from the osteoarthritis initiative. Journal of Orthopaedic Research, 35(10), 2243-2250.
  5. Avramidis, G. P., Avramidou, M. P., & Papakostas, G. A. (2022). Rheumatoid Arthritis Diagnosis: Deep Learning vs. Humane. Applied Sciences, 12(1), 10.
  6. Becker, A. (2019). Artificial intelligence in medicine: What is it doing for us today? Health Policy and Technology, 8(2), 198-205.
  7. Bengio, Y., & LeCun, Y. (2007). Scaling learning algorithms towards AI. Large-scale kernel machines, 34(5), 1-41.
  8. Bidgood Jr, W. D., Horii, S. C., Prior, F. W., & Van Syckle, D. E. (1997). Understanding and using DICOM, the data interchange standard for biomedical imaging. Journal of the American Medical Informatics Association, 4(3), 199-212.

Ayrıntılar

Birincil Dil

İngilizce

Konular

Mühendislik

Bölüm

Derleme

Erken Görünüm Tarihi

25 Aralık 2023

Yayımlanma Tarihi

31 Aralık 2023

Gönderilme Tarihi

29 Kasım 2022

Kabul Tarihi

10 Temmuz 2023

Yayımlandığı Sayı

Yıl 2023 Cilt: 16 Sayı: 3

Kaynak Göster

APA
Altıkardeş, Z. A., Canayaz, E., & Ünsal, A. (2023). Machine LearningDeep Learning in Rheumatological Screening A Systematic Review. Erzincan University Journal of Science and Technology, 16(3), 940-969. https://doi.org/10.18185/erzifbed.1211547
AMA
1.Altıkardeş ZA, Canayaz E, Ünsal A. Machine LearningDeep Learning in Rheumatological Screening A Systematic Review. Erzincan University Journal of Science and Technology. 2023;16(3):940-969. doi:10.18185/erzifbed.1211547
Chicago
Altıkardeş, Zehra Aysun, Emre Canayaz, ve Alparslan Ünsal. 2023. “Machine LearningDeep Learning in Rheumatological Screening A Systematic Review”. Erzincan University Journal of Science and Technology 16 (3): 940-69. https://doi.org/10.18185/erzifbed.1211547.
EndNote
Altıkardeş ZA, Canayaz E, Ünsal A (01 Aralık 2023) Machine LearningDeep Learning in Rheumatological Screening A Systematic Review. Erzincan University Journal of Science and Technology 16 3 940–969.
IEEE
[1]Z. A. Altıkardeş, E. Canayaz, ve A. Ünsal, “Machine LearningDeep Learning in Rheumatological Screening A Systematic Review”, Erzincan University Journal of Science and Technology, c. 16, sy 3, ss. 940–969, Ara. 2023, doi: 10.18185/erzifbed.1211547.
ISNAD
Altıkardeş, Zehra Aysun - Canayaz, Emre - Ünsal, Alparslan. “Machine LearningDeep Learning in Rheumatological Screening A Systematic Review”. Erzincan University Journal of Science and Technology 16/3 (01 Aralık 2023): 940-969. https://doi.org/10.18185/erzifbed.1211547.
JAMA
1.Altıkardeş ZA, Canayaz E, Ünsal A. Machine LearningDeep Learning in Rheumatological Screening A Systematic Review. Erzincan University Journal of Science and Technology. 2023;16:940–969.
MLA
Altıkardeş, Zehra Aysun, vd. “Machine LearningDeep Learning in Rheumatological Screening A Systematic Review”. Erzincan University Journal of Science and Technology, c. 16, sy 3, Aralık 2023, ss. 940-69, doi:10.18185/erzifbed.1211547.
Vancouver
1.Zehra Aysun Altıkardeş, Emre Canayaz, Alparslan Ünsal. Machine LearningDeep Learning in Rheumatological Screening A Systematic Review. Erzincan University Journal of Science and Technology. 01 Aralık 2023;16(3):940-69. doi:10.18185/erzifbed.1211547