Title :
Revised GMDH-type neural network using artificial intelligence and its application to medical image diagnosis
Author_Institution :
Grad. Sch. of Health Sci., Univ. of Tokushima, Tokushima, Japan
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;
Conference_Titel :
Hybrid Intelligent Models And Applications (HIMA), 2011 IEEE Workshop On
Conference_Location :
Paris
Print_ISBN :
978-1-4244-9907-6
DOI :
10.1109/HIMA.2011.5953960