The authors attempt to apply the back-propagation method (BP), described by Rumelhart and McClelland (1986), to dyspepsia diagnosis. In particular the program utilizes the method with adaptive learning parameters taken from the method adopted by Vogl (1988). The major aim is to identify patients who are suspected of having a neoplastic disease and need further diagnostic testing. The long term aim is to analyze patients suffering from various types of dyspepsia by which symptoms may be connected to pathologies with a low margin of error

An example of back propagation: Diagnosis of dyspepsia

P Arrigo;
1989

Abstract

The authors attempt to apply the back-propagation method (BP), described by Rumelhart and McClelland (1986), to dyspepsia diagnosis. In particular the program utilizes the method with adaptive learning parameters taken from the method adopted by Vogl (1988). The major aim is to identify patients who are suspected of having a neoplastic disease and need further diagnostic testing. The long term aim is to analyze patients suffering from various types of dyspepsia by which symptoms may be connected to pathologies with a low margin of error
1989
Istituto per lo Studio delle Macromolecole - ISMAC - Sede Milano
Neural Networks
medical diagnosis
backpropagation
File in questo prodotto:
Non ci sono file associati a questo prodotto.

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/201807
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus ND
  • ???jsp.display-item.citation.isi??? ND
social impact