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A total of 696 MR images (AS+: 348, AS\u2212: 348) were utilized for AS detection. Models were trained and tested on 70% of the dataset using a 10-fold cross-validation method to prevent overfitting, while the remaining 30% of the data was used for validation. In addition, care was taken to ensure that different images from the same patient were not split between the training and validation sets during this separation process to prevent potential data leakage.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>The proposed ML-based model demonstrated superior performance during the validation phase (accuracy: 0.885, AUC: 0.941). The results of our study show promising outcomes when compared to previous works employing GLCM-based ML detection models.<\/jats:p>\n                    <jats:p>\n                      <jats:bold>Conclusions:<\/jats:bold>\n                      This study introduces a new perspective on AS detection, focusing on the assignment of ML techniques to STIR-sequenced MR images with a notable absence of literature on interpreting ML models for AS detection. This typology also addresses a lack of knowledge, as most models do not provide practical interpretability or knowledge alongside accurate prediction. The system also offers an effective strategy for early and correct diagnosis of AS, which is important for timely intervention and treatment planning.\n                    <\/jats:p>\n                  <\/jats:sec>","DOI":"10.1177\/09287329241297887","type":"journal-article","created":{"date-parts":[[2025,2,10]],"date-time":"2025-02-10T10:18:16Z","timestamp":1739182696000},"page":"1182-1198","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":6,"title":["Development and validation of machine learning algorithms for early detection of ankylosing spondylitis using magnetic resonance images"],"prefix":"10.1177","volume":"33","author":[{"given":"Emre","family":"Canayaz","sequence":"first","affiliation":[{"name":"Vocational School of Technical Sciences, Marmara University, Istanbul, T\u00fcrkiye"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zehra Aysun","family":"Altikardes","sequence":"additional","affiliation":[{"name":"Department of Electrical and Electronics Engineering, Institute of Pure and Applied Sciences, Marmara University, Istanbul, Turkey"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Alparslan","family":"Unsal","sequence":"additional","affiliation":[{"name":"Faculty of Medicine, Department of Internal Medicine Division of Radiology, Aydin Adnan Menderes University, Aydin, Turkey"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hayriye","family":"Korkmaz","sequence":"additional","affiliation":[{"name":"Faculty of Technology, Electrical and Electronics Engineering, Department of Electrical and Electronics Engineering, Marmara University, Istanbul, Turkey"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mustafa","family":"Gok","sequence":"additional","affiliation":[{"name":"Faculty of Medicine, Department of Internal Medicine Division of Radiology, Aydin Adnan Menderes University, Aydin, Turkey"},{"name":"Faculty of Medicine, Department of Health Sciences, University of Sydney, Sydney, NSW, Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"179","published-online":{"date-parts":[[2024,12,29]]},"reference":[{"key":"e_1_3_4_2_2","article-title":"Diagnosis and treatment of ankylosing spondylitis","volume":"16","author":"Agrawal P","year":"2024","unstructured":"Agrawal P, Tote S, Sapkale B. 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