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medical datasets

Constraint based Cluster Ensemble to Detect Outliers in Medical Datasets

Constraint based Cluster Ensemble to Detect Outliers in Medical Datasets

... An outlier is an observation or pattern which exhibits a distinctively unusual behavior from other observations in the dataset. Outlier detection is an important data mining task of searching the database in order to ...

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Density Based Feature Selection Method for Medical Datasets

Density Based Feature Selection Method for Medical Datasets

... indicated that for large datasets, Naïve Bayes achieved higher AUC and lower FPR.Maciej Kusy [10] has analyzed the difficulties encountered in feature selection and feature extraction for classifying ...

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Visualization pipeline for medical datasets on grid computing environment

Visualization pipeline for medical datasets on grid computing environment

... the datasets more cumbersome using traditional desktop computers, where the conventional computer will be overwhelmed with intensive processing of large datasets even with the latest development of ...

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Remote visualization on medical datasets over thin clients with support of grid environment

Remote visualization on medical datasets over thin clients with support of grid environment

... processed datasets. However the continuous increase in the size of datasets and visualization operation causes insufficient performance with traditional desktop ...of datasets results an argent need ...

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Overlap-based undersampling method for classification of imbalanced medical datasets.

Overlap-based undersampling method for classification of imbalanced medical datasets.

... Rebalancing class distributions seems to be a typical approach to handle im- balanced medical datasets. However, it was shown in the literature that solutions based on improving the visibility of positive ...

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Privacy Preservation of Medical Datasets using Hadoop - A Survey

Privacy Preservation of Medical Datasets using Hadoop - A Survey

... ABSTRACT: As human dependency on computing services has increased in the past decade, privacy of datasets is a major concern. Privacy Preservation techniques need to be implemented in order to protect the ...

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The Utilisiation of composite Machine Learning models for the Classification of Medical Datasets For Sickle Cell Disease

The Utilisiation of composite Machine Learning models for the Classification of Medical Datasets For Sickle Cell Disease

... The models under study are composed of two types of integrated Machine learning algorithms: hybrid Neural Network with Levenberg-Marquardt learning algorithm [9], and Random Forest [9], combined using a further ...

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Wavelet Coding of Volumetric Medical Datasets

Wavelet Coding of Volumetric Medical Datasets

... In contrast to EZW, SPIHT and their related algorithms [25, 26], the coding algorithms presented in the following sections, including the standard JPEG2000-EBCOT coding algorithm [27], exploit only the intra-band ...

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Meta-Heuristic Approaches for the Classification of Medical Datasets Snegaa A 1, Dr. S. Sivakumari2

Meta-Heuristic Approaches for the Classification of Medical Datasets Snegaa A 1, Dr. S. Sivakumari2

... in medical environments leads to an exponential growth of clinical data extracted from heterogeneous patient ...several medical diagnosis and decision support ...

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Predicting The Heart Attack From Accessible Patients Medical Datasets Using Data Mining Technique

Predicting The Heart Attack From Accessible Patients Medical Datasets Using Data Mining Technique

... MI risk prediction models developed using baseline datasets with different sample age, and based on different prediction resolution combinations were analyzed. Cross validation was utilized during the training ...

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Evaluating privacy-preserving record linkage using cryptographic long-term keys and multibit trees on large medical datasets

Evaluating privacy-preserving record linkage using cryptographic long-term keys and multibit trees on large medical datasets

... Background: Integrating medical data using databases from different sources by record linkage is a powerful technique increasingly used in medical research. Under many jurisdictions, unique personal ...

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A Comprehensive Study of Clustering Algorithms to Analyze Medical Datasets

A Comprehensive Study of Clustering Algorithms to Analyze Medical Datasets

... The objective of this research work is focused on the ethical cluster creation of heart disease data and analyzed the performance of partition based algorithms. This research work would help the doctors to identify the ...

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Predictive Models for Bariatric Surgery Risks with Imbalanced Medical Datasets

Predictive Models for Bariatric Surgery Risks with Imbalanced Medical Datasets

... ley and Meyerhoefer [14], the national medical care costs of Obesity-related illnesses in adult pass more than $200 billion a year. Obesity, which is de- fined as having a Body Mass Index (BMI) of 30 Kg/m2), has ...

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Comparative study of medical datasets IETD and UCITD using statistical methods

Comparative study of medical datasets IETD and UCITD using statistical methods

... Recent studies indicated difference in classification accuracy of various classifiers. Proposed a comparative study by considering Indian e-Thyroid Dataset (IETD) from Indian e-TDML Repository and carried out univariate ...

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Handling limited datasets with neural networks in medical applications : a small data approach

Handling limited datasets with neural networks in medical applications : a small data approach

... small datasets, where such test data are scarce, the simple task of assessing generalisation becomes ...small medical datasets in general, thus the effect of dataset size on NN performance must be ...

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Exploring the Learnability of Numeric Datasets

Exploring the Learnability of Numeric Datasets

... the datasets become more difficult to be accurately ...these datasets range from rather low values to very high ...when datasets based on the Car evaluation dataset are considered, then almost always ...

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Effects of Distance between Classes and Training Datasets Size to the Performance of XCS: Case of Imbalance Datasets

Effects of Distance between Classes and Training Datasets Size to the Performance of XCS: Case of Imbalance Datasets

... The artificial datasets employed in the experiments have three major controlled parameters. The first one is distance between means of two classes in Gaussian distribution (dis), the second one is the training ...

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Performance Analysis of New Conversion Tool from          Relational Datasets to XML Datasets on Selected Websites

Performance Analysis of New Conversion Tool from Relational Datasets to XML Datasets on Selected Websites

... Performance analysis of the three data sets presented in the above experiments indicates that the efficiency of the system with respect to data access time is less when the data maintained in XML format than RDB. All the ...

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BiFold visualization of bipartite datasets

BiFold visualization of bipartite datasets

... For real datasets, the choice of methods for dealing with missing data can become a critical component of the data processing. In general, the BiFold approach admits a very reasoned approach that does not depend ...

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Tools for Mining Massive Datasets

Tools for Mining Massive Datasets

... In a 2001, Doug Laney,analyst for the Gartner Group, defined data challenges and opportunities as being three-dimensional: increasing volume (amount of data), velocity (speed of data [r] ...

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