DocumentCode
2298520
Title
Revised GMDH-type neural network using artificial intelligence and its application to medical image diagnosis
Author
Kondo, Tadashi
Author_Institution
Grad. Sch. of Health Sci., Univ. of Tokushima, Tokushima, Japan
fYear
2011
fDate
11-15 April 2011
Firstpage
76
Lastpage
83
Abstract
A revised Group Method of Data Handling (GMDH)-type neural network algorithm using artificial intelligence technology for medical image diagnosis is proposed and is applied to medical image diagnosis of lung cancer. In this algorithm, the knowledge base for medical image diagnosis is used for organizing the neural network architecture for medical image diagnosis. Furthermore, the revised GMDH-type neural network algorithm has a feedback loop and can identify the characteristics of the medical images accurately using feedback loop calculations. The optimum neural network architecture fitting the complexity of the medical images is automatically organized so as to minimize the prediction error criterion defined as Prediction Sum of Squares (PSS). It is shown that the revised GMDH-type neural network is accurate and a useful method for the medical image diagnosis of lung cancer.
Keywords
artificial intelligence; data handling; medical image processing; neural nets; artificial intelligence technology; feedback loop calculations; group method of data handling; lung cancer; medical image diagnosis; prediction sum of squares; revised GMDH-type neural network; Artificial neural networks; Cancer; Input variables; Lungs; Medical diagnostic imaging; Neurons; Artificial Intelligence; GMDH; Heuristic Self-Organization; Lung Cancer; Medical Image Diagnosis; Neural Networks;
fLanguage
English
Publisher
ieee
Conference_Titel
Hybrid Intelligent Models And Applications (HIMA), 2011 IEEE Workshop On
Conference_Location
Paris
Print_ISBN
978-1-4244-9907-6
Type
conf
DOI
10.1109/HIMA.2011.5953960
Filename
5953960
Link To Document