Myocardial infarction classification with multi-lead ECG using hidden Markov models and Gaussian mixture models
PC Chang, JJ Lin, JC Hsieh, J Weng - Applied Soft Computing, 2012 - Elsevier
This study presented a new diagnosis system for myocardial infarction classification by
converting multi-lead ECG data into a density model for increasing accuracy and flexibility of …
converting multi-lead ECG data into a density model for increasing accuracy and flexibility of …
Exploring nonlinear feature space dimension reduction and data representation in breast CADx with Laplacian eigenmaps and‐SNE
Purpose In this preliminary study, recently developed unsupervised nonlinear dimension
reduction (DR) and data representation techniques were applied to computer‐extracted …
reduction (DR) and data representation techniques were applied to computer‐extracted …
Learning grammatical structure with echo state networks
Echo State Networks (ESNs) have been shown to be effective for a number of tasks,
including motor control, dynamic time series prediction, and memorizing musical sequences …
including motor control, dynamic time series prediction, and memorizing musical sequences …
[图书][B] Data exploration process based on the self-organizing map
J Vesanto - 2002 - aaltodoc.aalto.fi
With the advances in computer technology, the amount of data that is obtained from various
sources and stored in electronic media is growing at exponential rates. Data mining is a …
sources and stored in electronic media is growing at exponential rates. Data mining is a …
Evaluating the impact of missing data imputation
A Pantanowitz, T Marwala - Advanced Data Mining and Applications: 5th …, 2009 - Springer
This paper presents an impact assessment for the imputation of missing data. The
assessment is performed by measuring the impacts of missing data on the statistical nature …
assessment is performed by measuring the impacts of missing data on the statistical nature …
Investigations of dipole localization accuracy in MEG using the bootstrap
We describe the use of the nonparametric bootstrap to investigate the accuracy of current
dipole localization from magnetoencephalography (MEG) studies of event-related neural …
dipole localization from magnetoencephalography (MEG) studies of event-related neural …
Enhancement of breast CADx with unlabeled data a
Purpose: Unlabeled medical image data are abundant, yet the process of converting them
into a labeled (“truth‐known”) database is time and resource expensive and fraught with …
into a labeled (“truth‐known”) database is time and resource expensive and fraught with …
Neural-network-based sensor data fusion for multi-hole fluid velocity probes
For measuring three components of velocity in unknown flow fields, multi-hole pressure
probes possess a significant advantage. Unlike methods such as hot-wire anemometry …
probes possess a significant advantage. Unlike methods such as hot-wire anemometry …
[PDF][PDF] Automatic recognition of light microscope pollen images
G Allen, B Hodgson, S Marsland, G Arnold, R Flemmer… - 2006 - core.ac.uk
This paper is a progress report on a project aimed at the realization of a low-cost, automatic,
trainable system “AutoStage” for recognition and counting of pollen. Previous work on image …
trainable system “AutoStage” for recognition and counting of pollen. Previous work on image …
[PDF][PDF] Modeling performance of different classification methods: deviation from the power law
S Singh - Project Report, Department of Computer Science …, 2005 - academia.edu
This project studied the effect of varying the training size for different classification
techniques. The learning curves were then regressed using four common equations. In the …
techniques. The learning curves were then regressed using four common equations. In the …