{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,18]],"date-time":"2026-06-18T06:46:40Z","timestamp":1781765200040,"version":"3.54.5"},"reference-count":40,"publisher":"Wiley","issue":"13-14","license":[{"start":{"date-parts":[[2024,7,10]],"date-time":"2024-07-10T00:00:00Z","timestamp":1720569600000},"content-version":"vor","delay-in-days":9,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0\/"}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Clinical Laboratory Analysis"],"published-print":{"date-parts":[[2024,7]]},"abstract":"<jats:title>ABSTRACT<\/jats:title><jats:sec><jats:title>Objective<\/jats:title><jats:p>In response to the nuanced glycemic challenges faced by women with iron deficiency anemia (IDA) associated with diabetes, this study uses advanced machine learning algorithms to redefine hemoglobin (Hb)A1c measurement values. We aimed to improve the accuracy of glycemic interpretation by recognizing the critical interaction between erythrocytes, iron, and glycemic levels in this specific demographic group.<\/jats:p><\/jats:sec><jats:sec><jats:title>Methods<\/jats:title><jats:p>This retrospective observational study included 17,526 adult women with HbA1c levels recorded from 2017 to 2022. Samples were classified as diabetic, prediabetic, or non\u2010diabetic based on HbA1c and fasting blood glucose (FBG) levels for distribution analysis without impacting model training. Support Vector Machines, Linear Regression, Random Forest, and K\u2010Nearest Neighbor algorithms as machine learning (ML) methods were used to predict HbA1c levels. Following the training of the model, HbA1c values were predicted for the IDA samples using the trained model.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>According to our results, there has been a 0.1 unit change in HbA1c values, which has resulted in a clinical decision change in some patients.<\/jats:p><\/jats:sec><jats:sec><jats:title>Discussion<\/jats:title><jats:p>Using ML to analyze HbA1c results in women with IDA may unveil distinctions among patients whose HbA1c values hover near critical medical decision thresholds. This intersection of technology and laboratory science holds promise for enhancing precision in medical decision\u2010making processes.<\/jats:p><\/jats:sec>","DOI":"10.1002\/jcla.25087","type":"journal-article","created":{"date-parts":[[2024,7,10]],"date-time":"2024-07-10T13:19:05Z","timestamp":1720617545000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Unlocking Optimal Glycemic Interpretation: Redefining <scp>HbA1c<\/scp> Analysis in Female Patients With Diabetes and Iron\u2010Deficiency Anemia Using Machine Learning Algorithms"],"prefix":"10.1002","volume":"38","author":[{"ORCID":"https:\/\/orcid.org\/0009-0006-0949-6980","authenticated-orcid":false,"given":"Kadra\u00a0Mohamed","family":"Abdillahi","sequence":"first","affiliation":[{"name":"Department of Biochemistry Faculty of Medicine, Kocaeli University  Kocaeli Turkey"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9410-8554","authenticated-orcid":false,"given":"Fatma\u00a0Ceyla","family":"Eraldemir","sequence":"additional","affiliation":[{"name":"Department of Biochemistry Faculty of Medicine, Kocaeli University  Kocaeli Turkey"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5219-5397","authenticated-orcid":false,"given":"Irfan","family":"K\u00f6sesoy","sequence":"additional","affiliation":[{"name":"Software Engineering, Faculty of Engineering Kocaeli University  Kocaeli Turkey"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2024,7,10]]},"reference":[{"key":"e_1_2_12_2_1","doi-asserted-by":"publisher","DOI":"10.2337\/dc22-S002"},{"issue":"6","key":"e_1_2_12_3_1","article-title":"The Effect of Anemia and the Goal of Optimal HbA1c Control in Diabetes and Non\u2010Diabetes","volume":"12","author":"Katwal P. 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