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Pattern Classification Techniques for Early Lung Cancer Diagnosis using an Electronic Nose
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Pattern Classification Techniques for Lung Cancer Diagnosis by an Electronic Nose.
No full textComputational intelligence techniques can be implemented to analyze the olfactory signal as perceived by an electronic nose, and to detect information to diagnose a multitude of human diseases. Our research suggests the use of an electronic nose to diagnose lung cancer. An electronic nose is able to acquire and recognize the volatile organic compounds (VOCs) present in the analyzed substance: it is composed of an array of electronic, chemical sensors, and a pattern classification module based on computational intelligence techniques. The three main stages characterizing the basic functioning of an electronic nose are: acquisition, preprocessing and pattern analysis. In the lung cancer detection experimentation, we analyzed 104 breath samples of 52 subjects, 22 healthy subjects and 30 patients with primary lung cancer at different stages. In order to find the best classification model able to discriminate between the two classes healthy and lung cancer subjects, and to reduce the dimensionality of the problem, we implemented a genetic algorithm (GA) that can find the best combination of feature selection, feature projection and classifier algorithms to be used. In particular, for feature projection, we considered Principal Component Analysis (PCA), Fisher Linear Discriminant Analysis (LDA) and Non Parametric Linear Discriminant Analysis (NPLDA); classification has been performed implementing several supervised pattern classification algorithms, based on different k-Nearest Neighbors (k-NN) approaches (classic, modified and fuzzy k-NN), on linear and quadratic discriminant functions classifiers and on a feed-forward Artificial Neural Network (ANN). The best solution provided from the genetic algorithm has been the projection of a subset of features into a single component using the Fisher Linear Discriminant Analysis and a classification based on the k-Nearest Neighbors method. The observed results, all validated using cross-validation, have been excellent achieving an average accuracy of 96.2%, an average sensitivity of 93.3% and an average specificity of 100%, as well as very small confidence intervals. We also investigated the possibility of performing early diagnosis, building a model able to predict a sample belonging to a subject with primary lung cancer at stage I compared to healthy subjects. Also in this analysis results have been very satisfactory, achieving an average accuracy of 92.85%, an average sensitivity of 75.5% and an average specificity of 97.72%. The achieved results demonstrate that the electronic nose, combined with the appropriate computational intelligence methodologies, is a promising alternative to current lung cancer diagnostic techniques: not only the instrument is completely non invasive, but the obtained predictive errors are lower than those achieved by present diagnostic methods, and the cost of the analysis, both in money, time and resources, is lower. The introduction of this cutting edge technology will lead to very important social and business effects: its low price and small dimensions allow a large scale distribution, giving the opportunity to perform non invasive, cheap, quick, and massive early diagnosis and screening
Going Beyond Counting First Authors in Author Co-citation Analysis
Get PDFThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Realizzazione e validazione di un sistema per la classificazione di movimenti immaginari in una interfaccia cervello-computer
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Variations on the Author
Get PDF“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Get PDFWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
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