The purpose of this study is to develop a clinical decision support system based on machine learning (ML) algorithms to help the diagnostic of chronic obstructive pulmonary disease (COPD) using forced oscillation (FO) measurements. To this end, the performances of classification algorithms based on Linear Bayes Normal Classifier, K nearest neighbor (KNN), decision trees, artificial neural netwo...

Two approaches to the classification of different locomotor activities performed at various speeds are here presented and evaluated: a maximum a posteriori (MAP) Bayes' classification scheme and a Support Vector Machine (SVM) are applied on a 2D projection of 16 features extracted from accelerometer data. The locomotor activities (level walking, stair climbing, and stair descending) were record...

An artificial neural network (ANN) is an information-processing paradigm that is designed to emulate some of the observed properties of the mammalian brain. First proposed in the early 1950's it was not until the technology revolution of the 1980's that a multitude of alternative ANN methods were spawned to solve a wide variety of complex real-world problems. Today, the contemporary literature ...

Motivation. In medical field, particularly the cardiology, the diagnosis systems constitute the essential domain of research. In some applications, the traditional methods of classification present some limitations. The neuronal technique is considered as one of the promising algorithms to resolve such problem. Method. In this paper, two approaches of the Artificial Neuronal Network (ANN) techn...

PURPOSE The goal of this study was to investigate the feasibility of differentiating brain metastases from different types of lung cancers using texture analysis (TA) of T1 postcontrast MR images. METHODS TA was performed, and four subset textures were extracted and calculated separately. The capability of each texture to classify the different types of lung carcinoma was investigated using t...

Curators of biological databases transfer knowledge from scientific publications, a laborious and expensive manual process. Machine learning algorithms can reduce the workload of curators by filtering relevant biomedical literature, though their widespread adoption will depend on the availability of intuitive tools that can be configured for a variety of tasks. We propose a new method for suppo...

Neural networks have been part of an attempt to emulate the learning curve of the human nervous system. Graphics Processing Units (GPUs) that come with a Graphics card have hundreds of processing cores, and have highly parallel architecture. Because of the highly parallel architecture of GPUs, it suits very well for parallel architecture such as Neural Network. In fact, GPUs have become a Gener...

The current method to classify graphite morphology types of grey cast iron is based on traditional subjective observation, and it cannot be used for quantitative analysis. Since microstructures have a great effect on the mechanical properties of grey cast iron and different types have totally different characters, six types of grey cast iron are discussed and an image-processing software subsys...

In this work, a new identification model, based on extreme learning machine (ELM), to better identify Erythemato – Squamous skin diseases have been proposed and implemented and the results compared to that of the classical artificial neural network (ANN). ELMs provide solutions to singleand multihidden layer feedforward neural networks. ELMs can achieve high learning speed, good generalization ...

We report results of an in-vitro autofluorescence spectroscopic study on formalin-fixed human breast tissue samples. The study involved tissue samples from 20 patients with breast cancer who underwent radical mastectomy at Choithram Hospital and Research Centre, Indore. A diagnostic algorithm making use of principal component analysis (PCA) as the feature extractor and artificial neural network...