Estimate of the homa-ir cut-off value for identifying subjects at risk of insulin resistance using a machine learning approach
المؤلفون المشاركون
Alya al-Ansari
Zadjali, Fahd
Abd al-Salam, Abd al-Hamid
Zidoum, Hamzah
Hedjam, Rashid
Bayoumi, Riad
al-Yahyai, Said
al-Barwani, Sulayma
المصدر
Sultan Qaboos University Medical Journal
العدد
المجلد 21، العدد 4 (30 نوفمبر/تشرين الثاني 2021)، ص ص. 604-612، 9ص.
الناشر
جامعة السلطان قابوس كلية الطب و العلوم الصحية
تاريخ النشر
2021-11-30
دولة النشر
سلطنة عمان
عدد الصفحات
9
التخصصات الرئيسية
الملخص EN
-This study describes an unsupervised machine learning approach used to estimate the homeostatic model assessment-insulin resistance (HOMA-IR) cut-off for identifying subjects at risk of IR in a given ethnic group based on the clinical data of a representative sample.
Methods: The approach was applied to analyse the clinical data of individuals with Arab ancestors, which was obtained from a family study conducted in Nizwa, Oman, between January 2000 and December 2004.
First, HOMA-IR-correlated variables were identified to which a clustering algorithm was applied.
Two clusters having the smallest overlap in their HOMA-IR values were retrieved.
These clusters represented the samples of two populations, which are insulin-sensitive subjects and individuals at risk of IR.
The cut-off value was estimated from intersections of the Gaussian functions, thereby modelling the HOMA-IR distributions of these populations.
Results: A HOMA-IR cut-off value of 1.62 ± 0.06 was identified.
The validity of this cut-off was demonstrated by showing the following: 1) that the clinical characteristics of the identified groups matched the published research findings regarding IR; 2) that a strong relationship exists between the segmentations resulting from the proposed cut-off and those resulting from the two-hour glucose cut-off recommended by the World Health Organization for detecting prediabetes.
Finally, the method was also able to identify the cut-off values for similar problems (e.g.
fasting sugar cut-off for prediabetes).
Conclusion: The proposed method defines a HOMA-IR cut-off value for detecting individuals at risk of IR.
Such methods can identify high-risk individuals at an early stage, which may prevent or delay the onset of chronic diseases such as type 2 diabetes.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Alya al-Ansari& Bayoumi, Riad; Bayoumi, Riad& al-Yahyai, Said& Hasan, Muhammad Usamah& al-Barwani, Sulayma…[et al.]. 2021. Estimate of the homa-ir cut-off value for identifying subjects at risk of insulin resistance using a machine learning approach. Sultan Qaboos University Medical Journal،Vol. 21, no. 4, pp.604-612.
https://search.emarefa.net/detail/BIM-1366415
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Hasan, Muhammad Usamah…[et al.]. Estimate of the homa-ir cut-off value for identifying subjects at risk of insulin resistance using a machine learning approach. Sultan Qaboos University Medical Journal Vol. 21, no. 4 (Nov. 2021), pp.604-612.
https://search.emarefa.net/detail/BIM-1366415
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Alya al-Ansari& Bayoumi, Riad; Bayoumi, Riad& al-Yahyai, Said& Hasan, Muhammad Usamah& al-Barwani, Sulayma…[et al.]. Estimate of the homa-ir cut-off value for identifying subjects at risk of insulin resistance using a machine learning approach. Sultan Qaboos University Medical Journal. 2021. Vol. 21, no. 4, pp.604-612.
https://search.emarefa.net/detail/BIM-1366415
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
رقم السجل
BIM-1366415
قاعدة معامل التأثير والاستشهادات المرجعية العربي "ارسيف Arcif"
أضخم قاعدة بيانات عربية للاستشهادات المرجعية للمجلات العلمية المحكمة الصادرة في العالم العربي
تقوم هذه الخدمة بالتحقق من التشابه أو الانتحال في الأبحاث والمقالات العلمية والأطروحات الجامعية والكتب والأبحاث باللغة العربية، وتحديد درجة التشابه أو أصالة الأعمال البحثية وحماية ملكيتها الفكرية. تعرف اكثر