PMID: 9161474Jan 1, 1997Paper

Focal liver disease: neural network-aided diagnosis based on clinical and laboratory data

Gastroentérologie Clinique Et Biologique
K RudzkiJ Rudzka

Abstract

The purpose of this study was to evaluate the use of clinical and laboratory data in the diagnosis of benign or malignant focal liver disease. Diagnosis was made by artificial neural network (NN), a system of simple computing units connected in a specific structural network. Seven clinical and laboratory variables were retrospectively studied in 172 patients with a liver mass (93 benign, 79 malignant) detected with ultrasound. The diagnostic efficacy of NN was compared with a score based on the logistic regression model (Beaujon score). Although the sensitivity of the Beaujon score and the neural network was similar (4 malignant tumors inversely classified), neural network-aided diagnosis was characterized by higher specificity and accuracy (respectively 98.9% vs 82.5%, P < 0.001, and 97.1% vs 88.4%, P < 0.002). In patients with a hepatic mass, neural network is a valuable method for differentiating malignant and benign tumors.

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