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R. S, M. S, Hasan MK, Saeed RA, Alsuhibany SA, Abdel-Khalek S. An Empirical Model to Predict the Diabetic Positive Using Stacked Ensemble Approach. Front Public Health 2022; 9:792124. [PMID: 35127623 PMCID: PMC8814448 DOI: 10.3389/fpubh.2021.792124] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/09/2021] [Accepted: 11/30/2021] [Indexed: 01/18/2023] Open
Abstract
Today, disease detection automation is widespread in healthcare systems. The diabetic disease is a significant problem that has spread widely all over the world. It is a genetic disease that causes trouble for human life throughout the lifespan. Every year the number of people with diabetes rises by millions, and this affects children too. The disease identification involves manual checking so far, and automation is a current trend in the medical field. Existing methods use a single algorithm for the prediction of diabetes. For complex problems, a single model is not enough because it may not be suitable for the input data or the parameters used in the approach. To solve complex problems, multiple algorithms are used. These multiple algorithms follow a homogeneous model or heterogeneous model. The homogeneous model means the same algorithm, but the model has been used multiple times. In the heterogeneous model, different algorithms are used. This paper adopts a heterogeneous ensemble model called the stacked ensemble model to predict whether a person has diabetes positively or negatively. This stacked ensemble model is advantageous in the prediction. Compared to other existing models such as logistic regression Naïve Bayes (72), (74.4), and LDA (81%), the proposed stacked ensemble model has achieved 93.1% accuracy in predicting blood sugar disease.
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Affiliation(s)
- Sivashankari R.
- School of Information Technology and Engineering, Vellore Institute of Technology (VIT), Vellore, India
| | - Sudha M.
- School of Information Technology and Engineering, Vellore Institute of Technology (VIT), Vellore, India
| | - Mohammad Kamrul Hasan
- Center for Cyber Security, Faculty of Information Science and Technology, Universiti Kebangsaan Malaysia, Bangi, Malaysia
- *Correspondence: Mohammad Kamrul Hasan ;
| | - Rashid A. Saeed
- Department of Computer Engineering, College of Computers and Information Technology, Taif University, Taif, Saudi Arabia
| | - Suliman A. Alsuhibany
- Department of Computer Science, College of Computer, Qassim University, Buraydah, Saudi Arabia
| | - Sayed Abdel-Khalek
- Mathematics and Statistics Department, College of Science, Taif University, Taif, Saudi Arabia
- Mathematics Department, Sohag University, Sohag, Egypt
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Salis S, Joseph M, Agarwala A, Sharma R, Kapoor N, Irani AJ. Medical nutrition therapy of pediatric type 1 diabetes mellitus in India: Unique aspects and challenges. Pediatr Diabetes 2021; 22:93-100. [PMID: 32666666 DOI: 10.1111/pedi.13080] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/08/2020] [Revised: 06/30/2020] [Accepted: 07/09/2020] [Indexed: 12/16/2022] Open
Abstract
Medical nutrition therapy (MNT) is a vital aspect of management of type 1 diabetes mellitus (T1DM) and should be tailored to ethnic and family traditions and the socioeconomic and educational status of the patient. In this article, we discuss the unique aspects of MNT in children and adolescents with T1DM in the Indian setting, with focus on the challenges faced by patients, dieticians and physicians and how these can be overcome. The authors reviewed the available literature on MNT in T1DM from India and prepared the document based on their vast collective clinical experience in treating patients with T1DM from different regions in India. Indian diets are predominantly carbohydrate-based with high glycemic index (GI) and low protein content. Various methods are available to increase the protein and fiber content and reduce the GI of food in order to limit glycemic excursions. Insulin regimens need to be tailored to the child's school timings, meal schedule, and the availability of a responsible adult to supervise/administer insulin. All patients, irrespective of economic and education background, should be taught the broad principles of healthy eating, balanced diet and carbohydrate counting. There are various barriers to dietary compliance, including joint family system, changing lifestyles, and other factors which need to be addressed. There is a need to customize dietary management according to patient characteristics and needs and develop standardized patient educational material on principles of healthy eating in various regional languages.
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Affiliation(s)
- Sheryl Salis
- Department of Nutrition, Nurture Health Solutions, Mumbai, Maharashtra, India
| | - Mini Joseph
- Department of Home Science, Government College for Women, Trivandrum, Kerala, India
| | - Anuja Agarwala
- Department of Pediatrics, All India Institute of Medical Sciences, New Delhi, India
| | - Rajni Sharma
- Division of Pediatric Endocrinology, Department of Pediatrics, All India Institute of Medical Sciences, New Delhi, India
| | - Nitin Kapoor
- Deptartment of Endocrinology, Diabetes and Metabolism, Christian Medical College, Vellore, Tamil Nadu, India.,NCD Unit, Melbourne School of Population and Global Health, Faculty of Medicine, Dentistry and Health Sciences, University of Melbourne, Melbourne, Australia
| | - Aspi J Irani
- Department of Pediatrics, Nanavati Super Speciality Hospital, Mumbai, India.,Juvenile Diabetes Foundation, Maharashtra Chapter, Mumbai, Maharashtra, India
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Affiliation(s)
- K. Sandhya Rani
- Department of Endocrinology, NMCH, Nellore, Andhra Pradesh, India
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