Literature DB >> 16488775

Utilization of artificial neural networks in the diagnosis of optic nerve diseases.

Sadik Kara1, Ayşegül Güven, Ayşe Oztürk Oner.   

Abstract

This research is concentrated on the diagnosis of optic nerve disease through the analysis of pattern electroretinography (PERG) signals with the help of artificial neural network (ANN). Multilayer feed forward ANN trained with a Levenberg Marquart (LM) backpropagation algorithm was implemented. The designed classification structure has about 96.4% sensitivity, 90.4% specifity and positive prediction is calculated to be 94.2%. The end results are classified as healthy and diseased. Testing results were found to be compliant with the expected results that are derived from the physician's direct diagnosis. The end benefit would be to assist the physician to make the final decision without hesitation.

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Mesh:

Year:  2006        PMID: 16488775     DOI: 10.1016/j.compbiomed.2005.01.003

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


  3 in total

1.  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

2.  Computer aided quantification for retinal lesions in patients with moderate and severe non-proliferative diabetic retinopathy: a retrospective cohort study.

Authors:  Huiqun Wu; Xiaofeng Zhang; Xingyun Geng; Jiancheng Dong; Guomin Zhou
Journal:  BMC Ophthalmol       Date:  2014-10-31       Impact factor: 2.209

3.  Comparison of Machine Learning Approaches to Improve Diagnosis of Optic Neuropathy Using Photopic Negative Response Measured Using a Handheld Device.

Authors:  Tina Diao; Fareshta Kushzad; Megh D Patel; Megha P Bindiganavale; Munam Wasi; Mykel J Kochenderfer; Heather E Moss
Journal:  Front Med (Lausanne)       Date:  2021-12-03
  3 in total

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