This paper demonstrates the capability of curve fitting using Artificial Neural Network (ANN), not only for a moderate set of input data but also for a coarse set of input. When appropriate number of neurons is chosen for the training purpose, accurate graphs can be obtained, despite having a coarse data. The effect of number of neurons used for curve fitting and the accuracy obtained is also s...

Background and Objectives: Gestational Diabetes Mellitus (GDM) is the most common metabolic disorder in pregnancy. In case of early detection, some of its complications can be prevented. The aim of this study was to investigate early prediction of GDM by logistic regression (LR), discriminant analysis (DA), decision tree (DT) and perceptron artificial neural network (ANN) and to compare these m...

Curve fitting for oscillometric waveforms is vital to maximum amplitude algorithm (MAA) in blood pressure measurement. Popular methods in recent years, such as asymmetric Gaussian or Lorentzian functions, perform well when the profile of the oscillometric waveforms (OMW) are close to them. But they will have a relatively large mean square error (MSE) when the oscillometric pulse amplitude envel...

A novel high-speed fluorescence lifetime imaging (FLIM) analysis method based on artificial neural networks (ANN) has been proposed. In terms of image generation, the proposed ANN-FLIM method does not require iterative searching procedures or initial conditions, and it can generate lifetime images at least 180-fold faster than conventional least squares curve-fitting software tools. The advanta...