Predicting blood glucose levels of diabetics using artificial neural networks

نویسنده

  • Peter Kok
چکیده

It is assumed that the reader has a basic knowledge of artificial neural networks, although this is not absolutely necessary. If you are not interested in the details of neural networks, chapters 1, 3.1-3.3, 4, 7 and 8 are recommended. Chapter 2 gives a detailed background of available research in diabetes management using various kinds of control systems. If you are only interested in the results, chapter 7 is also recommended besides chapters 1 and 8.

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Artificial neural networks: applications in predicting pancreatitis survival

Artificial neural networks are intelligent systems that have successfully been used for prediction in different medical fields. In this study, the efficiency of a neural network for predicting the survival of patients with acute pancreatitis is compared with days-of-survival obtained from patients. A three- layer back-propagation neural network was developed for this purpose. Clinical data (e.g...

متن کامل

Artificial neural networks: applications in predicting pancreatitis survival

Artificial neural networks are intelligent systems that have successfully been used for prediction in different medical fields. In this study, the efficiency of a neural network for predicting the survival of patients with acute pancreatitis is compared with days-of-survival obtained from patients. A three- layer back-propagation neural network was developed for this purpose. Clinical data (e.g...

متن کامل

Predicting the buckling Capacity of Steel Cylindrical Shells with Rectangular Stringers under Axial Loading by using Artificial Neural Networks

A parametric study was carried out in order to investigate the buckling capacity of the vertically stiffened cylindrical shells. To this end ANSYS software was used. Cylindrical steel shells with different yield stresses, diameter-to-thickness ratios (D/t) and number of stiffeners were modeled and their buckling capacities were calculated by displacement control nonlinear static analysis.  Radi...

متن کامل

Predicting the Grouting Ability of Sandy Soils by Artificial Neural Networks Based On Experimental Tests

In this paper, the grouting ability of sandy soils is investigated by artificial neural networks based on the results of chemical grout injection tests. In order to evaluate the soil grouting potential, experimental samples were prepared and then injected. The sand samples with three different particle sizes (medium, fine, and silty) and three relative densities (%30, %50, and %90) were injecte...

متن کامل

PREDICTION OF COMPRESSIVE STRENGTH AND DURABILITY OF HIGH PERFORMANCE CONCRETE BY ARTIFICIAL NEURAL NETWORKS

Neural networks have recently been widely used to model some of the human activities in many areas of civil engineering applications. In the present paper, artificial neural networks (ANN) for predicting compressive strength of cubes and durability of concrete containing metakaolin with fly ash and silica fume with fly ash are developed at the age of 3, 7, 28, 56 and 90 days. For building these...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2005