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Can Prototype-Based Classification be a good Method for Biomedical Applications?

by Suzanne Little, Sara Colatino, Ovidio Salvetti, Petra Perner
"... Abstract. Many medical diagnosis applications are characterized by datasets that contain under-represented classes due to the fact that the disease is much rarer than the normal case. In such a situation classifiers such as decision trees and Naïve Bayesian that generalize over the data are not the ..."
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are not the proper choice as classification methods. Case-based classifiers that can work on the samples seen so far are more appropriate for such a task. We propose to calculate the contingency table and class specific evaluation measures despite the overall accuracy for evaluation purposes of classifiers

Multiresolution grayscale and rotation invariant texture classification with local binary patterns

by Timo Ojala, Matti Pietikäinen, Topi Mäenpää - IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE , 2002
"... This paper presents a theoretically very simple, yet efficient, multiresolution approach to gray-scale and rotation invariant texture classification based on local binary patterns and nonparametric discrimination of sample and prototype distributions. The method is based on recognizing that certain ..."
Abstract - Cited by 1299 (39 self) - Add to MetaCart
This paper presents a theoretically very simple, yet efficient, multiresolution approach to gray-scale and rotation invariant texture classification based on local binary patterns and nonparametric discrimination of sample and prototype distributions. The method is based on recognizing

Locality-constrained linear coding for image classification

by Jinjun Wang, Jianchao Yang, Kai Yu, Fengjun Lv, Thomas Huang, Yihong Gong - IN: IEEE CONFERENCE ON COMPUTER VISION AND PATTERN CLASSIFICATOIN , 2010
"... The traditional SPM approach based on bag-of-features (BoF) requires nonlinear classifiers to achieve good image classification performance. This paper presents a simple but effective coding scheme called Locality-constrained Linear Coding (LLC) in place of the VQ coding in traditional SPM. LLC util ..."
Abstract - Cited by 443 (20 self) - Add to MetaCart
The traditional SPM approach based on bag-of-features (BoF) requires nonlinear classifiers to achieve good image classification performance. This paper presents a simple but effective coding scheme called Locality-constrained Linear Coding (LLC) in place of the VQ coding in traditional SPM. LLC

The strengthening the reporting of observational studies in epidemiology (STROBE) statement: guidelines for reporting observational studies.

by Erik Von Elm , Douglas G Altman , Matthias Egger , Stuart J Pocock , Peter C Gøtzsche , Jan P Vandenbroucke - PLoS Med , 2007
"... A B S T R A C T Much biomedical research is observational. The reporting of such research is often inadequate, which hampers the assessment of its strengths and weaknesses and of a study's generalisability. The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) Initi ..."
Abstract - Cited by 207 (1 self) - Add to MetaCart
A B S T R A C T Much biomedical research is observational. The reporting of such research is often inadequate, which hampers the assessment of its strengths and weaknesses and of a study's generalisability. The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE

Unsupervised Classification of Biomedical Abstracts using Lexical Association?

by Jonathon Read, Jonathan Webster, Alex Chengyu Fang
"... Abstract. The task of text classification is the assignment of labels that describe texts ’ char-acteristics, such as topic, genre or sentiment. Supervised machine learning techniques such as Support Vector Machines or the simple but effective Naı̈ve Bayes have been successfully ap-plied to this tas ..."
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-plied to this task. However, it is not always practical to acquire a sufficient corpus of labelled examples to train these methods. For these cases we describe an unsupervised method for text classification based on two hypotheses. Firstly, we propose that the class of a document may be determined by calculating its

Whom You Know Matters: Venture Capital Networks and Investment Performance,

by Yael Hochberg , Alexander Ljungqvist , Yang Lu , Steve Drucker , Jan Eberly , Eric Green , Yaniv Grinstein , Josh Lerner , Laura Lindsey , Max Maksimovic , Roni Michaely , Maureen O'hara , Ludo Phalippou Mitch Petersen , Jesper Sorensen , Per Strömberg Morten Sorensen , Yael Hochberg , Johnson - Journal of Finance , 2007
"... Abstract Many financial markets are characterized by strong relationships and networks, rather than arm's-length, spot-market transactions. We examine the performance consequences of this organizational choice in the context of relationships established when VCs syndicate portfolio company inv ..."
Abstract - Cited by 138 (8 self) - Add to MetaCart
focus on how each measure captures a slightly different aspect of a VC's economic role in the network. 3 See Wasserman and Faust (1997) for a detailed review of network analysis methods. 4 For tractability, the graph excludes biotech-focused VC firms that have no syndication relationships during

Support Vector Based Prototype Selection Method for Nearest Neighbor Rules

by Yuangui Li, Zhonghui Hu, Yunze Cai, Weidong Zhang
"... Abstract. The Support vector machines derive the class decision hyper planes from a few, selected prototypes, the support vectors (SVs) according to the principle of structure risk minimization, so they have good generalization ability. We proposed a new prototype selection method based on support v ..."
Abstract - Cited by 1 (0 self) - Add to MetaCart
Abstract. The Support vector machines derive the class decision hyper planes from a few, selected prototypes, the support vectors (SVs) according to the principle of structure risk minimization, so they have good generalization ability. We proposed a new prototype selection method based on support

APPLICATION OF F-REGRESSION METHOD TO FUZZY CLASSIFICATION PROBLEM

by Boris Izyumov
"... Abstract. In regression analysis, outliers always represent difficulties because they cause modeling errors. But under certain circumstances, they can actually contain useful information, as shown on the example of problem described in this article. That is why the task of outlier identification and ..."
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and analysis presents a twofold interest from the technical point of view. It is shown that f-regression method has good outlier detection capability and can be successfully applied to fuzzy classification problem.

An Effective General Purpose Approach for Automated Biomedical Document Classification

by unknown authors
"... Automated document classification can be a valuable tool for biomedical tasks that involve large amounts of text. However, in biomedicine, documents that have the desired properties are often rare, and special methods are usually required to address this issue. We propose and evaluate a method of cl ..."
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Automated document classification can be a valuable tool for biomedical tasks that involve large amounts of text. However, in biomedicine, documents that have the desired properties are often rare, and special methods are usually required to address this issue. We propose and evaluate a method

Techniques of EMG signal analysis: detection, processing, classification and Applications

by M. B. I. Reaz, M. S. Hussain, F. Mohd-yasin , 2006
"... Electromyography (EMG) signals can be used for clinical/biomedical applications, Evolvable Hardware Chip (EHW) development, and modern human computer interaction. EMG signals acquired from muscles require advanced methods for detection, decomposition, processing, and classification. The purpose of t ..."
Abstract - Cited by 48 (3 self) - Add to MetaCart
Electromyography (EMG) signals can be used for clinical/biomedical applications, Evolvable Hardware Chip (EHW) development, and modern human computer interaction. EMG signals acquired from muscles require advanced methods for detection, decomposition, processing, and classification. The purpose
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