The diagnosis of dyspepsia is very difficult because the symptoms are clinically aspecific and the gastric emptying time tests are of complex interpretation. An integrated and automated analysis of clinical and instrumental data may improve the diagnostic process. We present a database which has been set up to assist the clinician in the diagnosis of dyspepsia. The data base integrates a wide set of symptoms with data coming from laboratory tests. Moreover we assess the feasibility of classifying gastric emptying profiles using data on 66 subject as input of a unsupervised artificial neural network
SVGAS: a database to assist gastric emptying data analysis
GIACOMINI, MAURO;RUGGIERO, CARMELINA;MANSI, CARLO
1999-01-01
Abstract
The diagnosis of dyspepsia is very difficult because the symptoms are clinically aspecific and the gastric emptying time tests are of complex interpretation. An integrated and automated analysis of clinical and instrumental data may improve the diagnostic process. We present a database which has been set up to assist the clinician in the diagnosis of dyspepsia. The data base integrates a wide set of symptoms with data coming from laboratory tests. Moreover we assess the feasibility of classifying gastric emptying profiles using data on 66 subject as input of a unsupervised artificial neural network
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