Search results for "Data mining"

showing 10 items of 907 documents

Automated quality control protocol for MR spectra of brain tumors.

2008

Item does not contain fulltext eTUMOUR (http://www.etumour.net/) is acquiring a large database of brain tumor (1)H MR spectra to develop automated pattern recognition methods and decision support system (DSS) for tumor diagnosis. Development of accurate pattern-recognition algorithms requires spectra undistorted by artifacts, low signal-to-noise, or broad lines. eTUMOUR currently uses panels of expert spectroscopists to subjectively grade spectra as being acceptable or unacceptable. Automated quality control (QC) would be more satisfactory for several reasons: 1) to provide a reproducible objective classification of spectrum quality; 2) for use within the future DSS to prevent misdiagnosis …

Quality ControlProtocol (science)Decision support systemMagnetic Resonance SpectroscopyBrain NeoplasmsComputer sciencemedia_common.quotation_subjectFeature extractioncomputer.software_genreIndependent component analysisDecision Support TechniquesPattern Recognition AutomatedTest setPattern recognition (psychology)Support vector machine classifierHumansRadiology Nuclear Medicine and imagingQuality (business)Functional Imaging [UMCN 1.1]Data miningcomputermedia_commonMagnetic Resonance in Medicine
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Identification of patterns og change on mongitudinal data, illustrated by two exemples : study of hospital pathways in the management of cancer. Cons…

2014

Context In healthcare domain, data mining for knowledge discovery represent a growing issue. Questions about the organisation of healthcare system and the study of the relation between treatment and quality of life (QoL) perceived could be addressed that way. The evolution of technologies provides us with efficient data mining tools and statistical packages containing advanced methods available for non-experts. We illustrate this approach through two issues: 1 / What organisation of healthcare system for cancer diseases management? 2 / Exploring in patients suffering from metastatic cancer, the relationship between health-related QoL perceived and treatment received as part of a clinical tr…

Quality of lifeQualité de viesTrajectoire de soins[SDV.MHEP] Life Sciences [q-bio]/Human health and pathologyMultiple imputationImputation de donnéesFouille de donnéesClassificationCancersData miningTrajectory of careClusteringCancer
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On using novel “Anti-Bayesian” techniques for the classification of dynamical data streams

2017

The classification of dynamical data streams is among the most complex problems encountered in classification. This is, firstly, because the distribution of the data streams is non-stationary, and it changes without any prior “warning”. Secondly, the manner in which it changes is also unknown. Thirdly, and more interestingly, the model operates with the assumption that the correct classes of previously-classified patterns become available at a juncture after their appearance. This paper pioneers the use of unreported novel schemes that can classify such dynamical data streams by invoking the recently-introduced “Anti-Bayesian” (AB) techniques. Contrary to the Bayesian paradigm, that compare…

QuantilesComputer scienceData stream miningBayesian probability02 engineering and technologyClassificationcomputer.software_genreAnti-Bayesian classificationRobustness (computer science)020204 information systems0202 electrical engineering electronic engineering information engineering020201 artificial intelligence & image processingData miningcomputerBayesian paradigmQuantile2017 IEEE Congress on Evolutionary Computation (CEC)
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Molecular topology as a novel approach for drug discovery

2012

Molecular topology (MT) has emerged in recent years as a powerful approach for the in silico generation of new drugs. One key part of MT is that, in the process of drug design/discovery, there is no need for an explicit knowledge of a drug's mechanism of action unlike other drug discovery methods.In this review, the authors introduce the topic by explaining briefly the most common methodology used today in drug design/discovery and address the most important concepts of MT and the methodology followed (QSAR equations, LDA, etc.). Furthermore, the significant results achieved, from this approach, are outlined and discussed.The results outlined herein can be explained by considering that MT r…

Quantitative structure–activity relationshipDrug IndustryDrug discoveryProcess (engineering)Computer sciencebusiness.industryIn silicoQuantitative Structure-Activity RelationshipModels TheoreticalMachine learningcomputer.software_genreField (computer science)Pharmaceutical PreparationsDrug DesignDrug DiscoveryKey (cryptography)AnimalsComputer-Aided DesignHumansData miningArtificial intelligenceExplicit knowledgeMolecular topologybusinesscomputerExpert Opinion on Drug Discovery
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Retrained Classification of Tyrosinase Inhibitors and “In Silico” Potency Estimation by Using Atom-Type Linear Indices

2012

In this paper, the authors present an effort to increase the applicability domain (AD) by means of retraining models using a database of 701 great dissimilar molecules presenting anti-tyrosinase activity and 728 drugs with other uses. Atom-based linear indices and best subset linear discriminant analysis (LDA) were used to develop individual classification models. Eighteen individual classification-based QSAR models for the tyrosinase inhibitory activity were obtained with global accuracy varying from 88.15-91.60% in the training set and values of Matthews correlation coefficients (C) varying from 0.76-0.82. The external validation set shows globally classifications above 85.99% and 0.72 fo…

Quantitative structure–activity relationshipEngineeringSpeedupbusiness.industryIn silicoAtom (order theory)Pattern recognitionLinear discriminant analysiscomputer.software_genreSet (abstract data type)Artificial intelligenceData miningbusinesscomputerSelection (genetic algorithm)Applicability domainInternational Journal of Chemoinformatics and Chemical Engineering
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Similarity boosted quantitative structure-activity relationship--a systematic study of enhancing structural descriptors by molecular similarity.

2013

The concept of molecular similarity is one of the most central in the fields of predictive toxicology and quantitative structure-activity relationship (QSAR) research. Many toxicological responses result from a multimechanistic process and, consequently, structural diversity among the active compounds is likely. Combining this knowledge, we introduce similarity boosted QSAR modeling, where we calculate molecular descriptors using similarities with respect to representative reference compounds to aid a statistical learning algorithm in distinguishing between different structural classes. We present three approaches for the selection of reference compounds, one by literature search and two by…

Quantitative structure–activity relationshipInformaticsbusiness.industryStatistical learningGeneral Chemical EngineeringStructural diversityQuantitative Structure-Activity RelationshipPattern recognitionGeneral ChemistryPredictive toxicologyLibrary and Information Sciencescomputer.software_genreToxicologyComputer Science ApplicationsSimilarity (network science)Molecular descriptorArtificial intelligenceData miningbusinessCluster analysiscomputerMathematicsJournal of chemical information and modeling
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Combined use of PCA and QSAR/QSPR to predict the drugs mechanism of action. An application to the NCI ACAM Database

2009

During the years the National Cancer Institute (NCI) accumulated an enormous amount of information through the application of a complex protocol of drugs screening involving several tumor cell lines, grouped into panels according to the disease class. The Anti-cancer Agent Mechanism (ACAM) database is a set of 122 compounds with anti-cancer activity and a reasonably well known mechanism of action, for which are available drug screening data that measure their ability to inhibit growth of a panel of 60 human tumor lines, explicitly designed as a training set for neural network and multivariate analysis. The aim of this work is to adapt a methodology (previously developed for the analysis of …

Quantitative structure–activity relationshipMultivariate analysisDatabaseArtificial neural networkMechanism (biology)Computer scienceOrganic Chemistrycomputer.software_genreSettore CHIM/08 - Chimica FarmaceuticaComputer Science ApplicationsSet (abstract data type)Mechanism of actionTest setDrug DiscoveryPrincipal component analysisAnti-cancer Agent Mechanism database PCA QSAR/QSPR Mechanism of actionmedicineData miningmedicine.symptomcomputer
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Ab Initio Modeling of Donor–Acceptor Interactions and Charge-Transfer Excitations in Molecular Complexes: The Case of Terthiophene–Tetracyanoquinodim…

2015

This work presents a thorough quantum chemical study of the terthiophene-tetracyanoquinodimethane complex as a model for π-π donor-acceptor systems. Dispersion-corrected hybrid (B3LYP-D) and double hybrid (B2PLYP-D), hybrid meta (M06-2X and M06-HF), and recently proposed long-range corrected (LC-wPBE, CAM-B3LYP, and wB97X-D) functionals have been chosen to deal with π-π intermolecular interactions and charge-transfer excitations in a balanced way. These properties are exhaustively compared to those computed with high-level ab initio SCS-MP2 and CASPT2 methods. The wB97X-D functional exhibits the best performance. It provides reliable intermolecular distances and interaction energies and pre…

Quantum chemicalChemistryAb initioCharge (physics)computer.software_genreTetracyanoquinodimethaneComputer Science Applicationschemistry.chemical_compoundTerthiopheneChemical physicsData miningPhysical and Theoretical ChemistryDonor acceptorcomputerJournal of Chemical Theory and Computation
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Analyzing assessors and products in sorting tasks: DISTATIS, theory and applications

2007

Abstract In this paper we present a new method called distatis that can be applied to the analysis of sorting data. D istatis is a generalization of classical multidimensional scaling which allows one to analyze 3-ways distance tables. When used for analyzing sorting tasks, distatis takes into account individual sorting data. Specifically, when distatis is used to analyze the results of an experiment in which several assessors sort a set of products, we obtain two types of maps: One for the assessors and one for the products. In these maps, the proximity between two points reflects their similarity, and therefore these maps can be read using the same rules as standard metric multidimensiona…

RV coefficientNutrition and DieteticsSimilarity (geometry)GeneralizationSortingcomputer.software_genreSet (abstract data type)Metric (mathematics)sortData miningMultidimensional scalingAlgorithmcomputerFood ScienceMathematicsFood Quality and Preference
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"Osteolipoma of buccal mucosa: Case report and literature review"

2016

Osteolipoma affecting oral cavity is indeed rare. We hereby report a case of osteolipoma affecting buccal mucosa. A review of literature of osteolipoma of oral cavity, particularly on radiographic/imaging findings was done. Only 16 cases of Osteolipoma of oral cavity are reported in the literature. The radiographic findings of our case, i.e. multiple dense homogenous radio-opaque structures was reported earlier only in one case [out of 16] of osteolipoma of oral cavity. Key words:Lipoma, osteolipoma, panoramic radiography, radio-opaque, radiography.

RadiographyDentistryOdontologíaCase ReportOral cavitycomputer.software_genreBuccal mucosa03 medical and health sciences0302 clinical medicineOsteolipomaMedicineGeneral DentistryOral Medicine and Pathologybusiness.industry030206 dentistryLipoma:CIENCIAS MÉDICAS [UNESCO]medicine.diseaseCiencias de la saludstomatognathic diseases030220 oncology & carcinogenesisUNESCO::CIENCIAS MÉDICASData miningbusinesscomputerJournal of Clinical and Experimental Dentistry
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