Literature DB >> 15890326

Utilization of artificial neural networks and autoregressive modeling in diagnosing mitral valve stenosis.

Sadik Kara1, Ayşegül Güven, Mustafa Okandan, Fatma Dirgenali.   

Abstract

This research is concentrated on the diagnosis of mitral heart valve stenosis through the analysis of Doppler Signals' AR power spectral density graphic with the help of ANN. Multilayer feedforward ANN trained with a Levenberg Marquart backpropagation algorithm was implemented in the MATLAB environment. Correct classification of 94% was achieved, whereas 4 false classifications have been observed for the test group of 68 subjects in total. The designed classification structure has about 97.3% sensitivity, 90.3% specifity and positive prediction is calculated to be 92.3%. The stated results show that the proposed method can make an effective interpretation.

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Year:  2006        PMID: 15890326     DOI: 10.1016/j.compbiomed.2005.01.007

Source DB:  PubMed          Journal:  Comput Biol Med        ISSN: 0010-4825            Impact factor:   4.589


  3 in total

1.  Quantitative structure-retention relationship for retention behavior of organic pollutants in textile wastewaters and landfill leachate in LC-APCI-MS.

Authors:  Hadi Noorizadeh; Abbas Farmany
Journal:  Environ Sci Pollut Res Int       Date:  2011-11-11       Impact factor: 4.223

2.  Neural network-based diagnosing for optic nerve disease from visual-evoked potential.

Authors:  Sadik Kara; Ayşegül Güven
Journal:  J Med Syst       Date:  2007-10       Impact factor: 4.460

3.  Artificial intelligence in hospitals: providing a status quo of ethical considerations in academia to guide future research.

Authors:  Milad Mirbabaie; Lennart Hofeditz; Nicholas R J Frick; Stefan Stieglitz
Journal:  AI Soc       Date:  2021-06-28
  3 in total

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