Stacking-based multi-objective evolutionary ensemble framework for prediction of diabetes mellitus

2020 ◽  
Vol 40 (1) ◽  
pp. 1-22 ◽  
Author(s):  
Namrata Singh ◽  
Pradeep Singh
1996 ◽  
Vol 34 ◽  
pp. S7-S11
Author(s):  
C ITO ◽  
R MAEDA ◽  
K NAKAMURA ◽  
H SASAKI

2021 ◽  
Vol 9 ◽  
Author(s):  
Theodoros Argyropoulos ◽  
Emmanouil Korakas ◽  
Aristofanis Gikas ◽  
Aikaterini Kountouri ◽  
Stavroula Kostaridou-Nikolopoulou ◽  
...  

Hyperglycemia is a common manifestation in the course of severe disease and is the result of acute metabolic and hormonal changes associated with various factors such as trauma, stress, surgery, or infection. Numerous studies demonstrate the association of adverse clinical events with stress hyperglycemia. This article briefly describes the pathophysiological mechanisms which lead to hyperglycemia under stressful circumstances particularly in the pediatric and adolescent population. The importance of prevention of hyperglycemia, especially for children, is emphasized and the existing models for the prediction of diabetes are presented. The available studies on the association between stress hyperglycemia and progress to type 1 diabetes mellitus are presented, implying a possible role for stress hyperglycemia as part of a broader prognostic model for the prediction and prevention of overt disease in susceptible patients.


Author(s):  
Sai Lakshmi Nikhita Sagi ◽  
Mamatha Narsapuram ◽  
Pravallika Nakarikanti ◽  
Sahithi Sane ◽  
Sai Sudha Vadisina ◽  
...  

2020 ◽  
Vol 17 (8) ◽  
pp. 3449-3452
Author(s):  
M. S. Roobini ◽  
Y. Sai Satwick ◽  
A. Anil Kumar Reddy ◽  
M. Lakshmi ◽  
D. Deepa ◽  
...  

In today’s world diabetes is the major health challenges in India. It is a group of a syndrome that results in too much sugar in the blood. It is a protracted condition that affects the way the body mechanizes the blood sugar. Prevention and prediction of diabetes mellitus is increasingly gaining interest in medical sciences. The aim is how to predict at an early stage of diabetes using different machine learning techniques. In this paper basically, we use well-known classification that are Decision tree, K-Nearest Neighbors, Support Vector Machine, and Random forest. These classification techniques used with Pima Indians diabetes dataset. Therefore, we predict diabetes at different stage and analyze the performance of different classification techniques. We Also proposed a conceptual model for the prediction of diabetes mellitus using different machine learning techniques. In this paper we also compare the accuracy of the different machine learning techniques to finding the diabetes mellitus at early stage.


2021 ◽  
Vol 1 (2) ◽  
pp. 123-128
Author(s):  
Nurleli Idayati ◽  
Hidayatullah Hidayatullah ◽  
Cecep Maulana

Abstract: Diabetes mellitus drugs using Decision Support System (DSS) techniques. The DSS method used is the Multi Objective Optimization method on the basis of ratio analysis (MOORA). The data used in the study are data sourced from BPS in ther Kisaran city area. Application development uses web and MySQL database as a help tool to test the ranking results on the selection of Diabetes mellitus drugs. The results of this study are expected to provide better results in helping to determine the best Keywords : Decision Support System;MOORA Method;Diabetes mellitus;Drug Selection;Kisaran City Abstrak: obat Diabetes melitus dengan menggunakan teknik Sistem Pendukung Keputusan (SPK). Metode SPK yang digunakan adalah metode Multi Objective Optimization On The Basis Of Ratio Analysis (MOORA). Data yang digunakan dalam penelitian adalah data bersumber dari BPS di wilayah kota Kisaran. Pengembangan aplikasi menggunakan web dan database MySQL sebagai perangkat bantuan untuk menguji hasil perangkingan pada pemilihan obat Diabetes melitus. Hasil dari penelitian ini diharapkan dapat memberikan hasil yang lebih baik dalam membantu menentukan obat diabetes terbaik Kata Kunci : Sistem Pendukung Keputusan;Metode MOORA;Diabetes mellitus;Pemilihan Obat;Kota Kisaran


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