Artificial neural networks in medical decision making systems: an application to pulmonary diseases´ diagnosis through VHDL synthesis

Author

Economou, G.-P.K. ; Hallas, J.A. ; Mariatos, E.P. ; Goutis, C.E.

Author_Institution

VLSI Design Lab., Patras Univ., Greece

fYear

1995

fDate

6-9 Mar 1995

Firstpage

590

Abstract

A prototype medical decision making system (MDMS) based on a powerful subclass of artificial neural networks (ANNs) and its hardware description using VHDL, is the topic of this article. This MDMS, is generally structured to cover a whole category of distressed body organs. An application to the full spectrum of pulmonary diseases (PDs) is presented, whereas the ANNs that compose this MDMS have been taught by using real-world patients´ clinical data. The VHDL language provides the means to both realize the proposed platform and optimize the synthesized implementation hardware

Keywords

lung; medical diagnostic computing; VHDL synthesis; artificial neural networks; distressed body organs; pulmonary diseases´ diagnosis; real-world patients´ clinical data; synthesized implementation hardware optimization; Artificial neural networks; Decision making; Diseases; Humans; Intelligent networks; Laboratories; Medical diagnostic imaging; Network synthesis; Neural networks; Very large scale integration;

fLanguage

English

Publisher

ieee

Conference_Titel

European Design and Test Conference, 1995. ED&TC 1995, Proceedings.

Conference_Location

Paris

Print_ISBN

0-8186-7039-8

Type

conf

DOI

10.1109/EDTC.1995.470338

Filename

470338