[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-122492-en":3,"doc-seo-122492-105":30,"detail-sidebar-cat-0-en-105":91},{"code":4,"msg":5,"data":6},0,"success",{"doc_id":7,"user_id":8,"nickname":9,"user_avatar":10,"doc_module":4,"category_id":11,"category_name":12,"doc_title":13,"doc_description":14,"doc_content":15,"file_id":16,"file_url":17,"file_type":18,"file_size":19,"view_count":20,"is_deleted":4,"is_public":20,"is_downloadable":20,"audit_status":20,"page_count":21,"language":22,"language_code":23,"site_id":24,"html_lang":23,"table_of_contents":25,"faqs":26,"seo_title":27,"seo_description":14,"update_tm":28,"read_time":29},122492,1374391974585,"Genevieve","https://ap-avatar.wpscdn.com/davatar_276721f389ce27ea32af1340a28f341c",8,"Research & Report","Systematic Literature Review of Machine Learning Methods in Insulin Secretion Model Analysis - Main research article","Endogenous insulin secretion (UN) is essential for maintaining glucose homeostasis, while pathological changes enable earlier detection of metabolic dysfunction before diabetes mellitus develops. Because no gold standard exists for the UN profile, most studies rely on deconvolution of C-peptide measurements, leveraging equimolar co-secretion with insulin from pancreatic β-cells. This review searches machine learning-based modelling strategies used to build UN models and determine whether UN-derived data can quantify normal, pre-diabetic, or T2D metabolic states.","Systematic Literature Review of Machine Learning Methods in Insulin Secretion Model Analysis  \nMohd Hussaini Abbas, Nor Azlan Othman *, Samsul Setumin, Nor Salwa Damanhuri, Rohaiza Baharudin, Nur Sa’adah Muhamad Sauki and Sarah Addyani Shamsuddin  \nAbstract— Endogenous insulin secretion (UN) plays a critical role in maintaining glucose homeostasis. Pathological changes in UN enable early detection of metabolic inefficiency prior to the onset of diabetes mellitus (DM). Numerous researches have been carried out to establish the most effective method for assessing the participant’s glycemic state by identifying their UN profile. In contrast to insulin sensitivity (SI), there is no gold standard for UN profile. Thus, the deconvolution of C-peptide measurements is used in the majority of research to identify the UN profile. Due to the fact that C-peptide and insulin are co-secreted equimolarly from pancreatic β-cells, the latter method is shown to be accurate. Although studies have shown that the machine learning-based strategies can yield very positive outcomes in other areas of DM diagnosis, there is currently little research that employing machine learning for quantifying the UN profile to enable early diagnosis of metabolic dysfunction. Hence, the main objective of this study is to conduct a thorough search on machine learning-based modelling strategies that were used to identify the individualspecific UN profile through the development of a UN model. Additionally, this study will investigate whether the data acquired from the UN model can be used to quantify a person’s metabolic condition (either normal, pre-diabetic or T2D). The literature search turned up prospective studies linking machine learning and UN in its search and analysis. Meta-analyses summarize the available data and highlight various methodological stances. Thus, the exploratory of machine learning classification and regression technique can be portrayed in 3 different scenarios during the identification of UN profile. The 3 scenarios are: the study of insulin secretion through analyzing the insulin sensitivity, the study of UN without taking into considerations or in-depth study of U1 and U2, and the study of insulin secretion using deconvolution of plasma C-peptide concentrations. It is evident that while Decision Tree (DT) is ideal for the first scenario, Random Forest (RF) is the better option for the other two scenarios. Further optimization can be implemented with the use of these techniques under supervised learning to improve diagnosis and comprehend the pathogenesis of diabetes, particularly in UN.  \nIndex Terms—diabetes, insulin secretion, machine learning.  \nThis manuscript is submitted on 23rd Feb 2023 and accepted on 24th July 2023. Mohd Hussaini Abbas, Nor Azlan Othman, Samsul Setumin, Nor Salwa Damanhuri, Rohaiza Baharudin, Nur Sa’adah Muhamad Sauki and Sarah Addyani Shamsuddin are with Electrical Engineering Studies, College of Engineering, Universiti Teknologi MARA Cawangan Pulau Pinang, Kampus Permatang Pauh, 13500 Permatang Pauh,Pulau Pinang, Malaysia  \n*Corresponding author  \nEmail address: [azlan253@uitm.edu.my](azlan253@uitm.edu.my)  \n1985-5389/© 2023 The Authors. Published by UiTM Press. This is an open access article under the CC BY-NC-ND license ([http://creativecommons.org/](http://creativecommons.org/)[ ](http://creativecommons.org/)[licenses/by-nc-nd/4.0/](licenses/by-nc-nd/4.0/)) .  \nI. INTRODUCTION  \nDIABETES Mellitus disease is becoming more prevalent  \naround the world, with the number of cases increasing atan alarming rate. Diabetes now affects over 420 million people globally, making it one of the leading causes of death [1] . In Malaysia, citizen habits of consuming a high-sugar diet have put them at risk of diabetes as early as the age of 18 [2] .  \nCommonly, Malaysian consumes lots of rice-based meal throughout their daily diet. Studies show that high consumptions of rice-based meals, especially white rice, leads to a high i","cbCaim8uQL0mPsnP","https://ap.wps.com/l/cbCaim8uQL0mPsnP","pdf",478755,1,10,"English","en",105,"# Introduction\n## Diabetes\n## Insulin secretion and glucose homeostasis","[{\"question\":\"Why is endogenous insulin secretion (UN) important in metabolic monitoring?\",\"answer\":\"UN maintains glucose homeostasis. Changes in UN can indicate metabolic inefficiency before diabetes mellitus onset.\"},{\"question\":\"Why do many studies use C-peptide deconvolution instead of a direct UN gold standard?\",\"answer\":\"There is no gold standard for UN profile. Since C-peptide and insulin are co-secreted equimolarly from pancreatic β-cells, deconvolution of C-peptide is used to identify UN profiles.\"},{\"question\":\"How does this review categorize machine learning approaches for UN profile identification?\",\"answer\":\"It describes three scenarios: using insulin sensitivity analysis, studying UN without detailed consideration of U1/U2, and studying insulin secretion using deconvolution of plasma C-peptide. Decision Tree fits the first scenario, while Random Forest performs better in the other two.\"}]","Systematic Literature Review of Machine Learning Methods in Insulin Secretion Model Analysis - Main research article | PDF",1785810935,25,{"code":4,"msg":31,"data":32},"ok",{"site_id":24,"language":23,"slug":33,"title":13,"keywords":34,"description":14,"schema_data":35,"social_meta":86,"head_meta":88,"extra_data":90,"updated_unix":28},"systematic-literature-review-of-machine-learning-methods-in-insulin-secretion-model-analysis-main-research-article","",{"@graph":36,"@context":85},[37,54,68],{"@type":38,"itemListElement":39},"BreadcrumbList",[40,44,48,51],{"item":41,"name":42,"@type":43,"position":20},"https://docshare.wps.com","Home","ListItem",{"item":45,"name":46,"@type":43,"position":47},"https://docshare.wps.com/document/","Document",2,{"item":49,"name":12,"@type":43,"position":50},"https://docshare.wps.com/document/research-report/",3,{"item":52,"name":13,"@type":43,"position":53},"https://docshare.wps.com/document/systematic-literature-review-of-machine-learning-methods-in-insulin-secretion-model-analysis-main-research-article/122492/",4,{"url":52,"name":13,"@type":55,"author":56,"headline":13,"publisher":58,"fileFormat":61,"inLanguage":23,"description":14,"dateModified":62,"datePublished":62,"encodingFormat":61,"isAccessibleForFree":63,"interactionStatistic":64},"DigitalDocument",{"name":9,"@type":57},"Person",{"url":41,"name":59,"@type":60},"DocShare","Organization","application/pdf","2026-08-04",true,{"@type":65,"interactionType":66,"userInteractionCount":20},"InteractionCounter",{"@type":67},"ViewAction",{"@type":69,"mainEntity":70},"FAQPage",[71,77,81],{"name":72,"@type":73,"acceptedAnswer":74},"Why is endogenous insulin secretion (UN) important in metabolic monitoring?","Question",{"text":75,"@type":76},"UN maintains glucose homeostasis. Changes in UN can indicate metabolic inefficiency before diabetes mellitus onset.","Answer",{"name":78,"@type":73,"acceptedAnswer":79},"Why do many studies use C-peptide deconvolution instead of a direct UN gold standard?",{"text":80,"@type":76},"There is no gold standard for UN profile. Since C-peptide and insulin are co-secreted equimolarly from pancreatic β-cells, deconvolution of C-peptide is used to identify UN profiles.",{"name":82,"@type":73,"acceptedAnswer":83},"How does this review categorize machine learning approaches for UN profile identification?",{"text":84,"@type":76},"It describes three scenarios: using insulin sensitivity analysis, studying UN without detailed consideration of U1/U2, and studying insulin secretion using deconvolution of plasma C-peptide. 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