Background and aims. Recurrence after curative treatments of hepatocellular carcinoma on cirrhosis, strongly depends on tumor pathological features such as nuclear grade and microscopic vascular invasion but these data are accurately assessable only on the final surgical specimens. Aim of the present study was to develop an artificial neural network (ANN, a tool showing its greatest strength in case of non linear relationships), able to predict tumor grade and microvascular invasion on the basis of preoperative variables.

Can Hepatocellular Carcinoma tumor grade and microscopical vascular invasion be predicted with an artificial neural network? / Cucchetti A; Piscaglia F; D'Errico A; Ravaioli M; Cescon M; Zanello M; Vivarelli M; Ercolani G; Grazi GL; Golfieri R; Pinna AD. - In: DIGESTIVE AND LIVER DISEASE. - ISSN 1590-8658. - STAMPA. - 41:(2009), pp. 7-7. [10.1016/j.dld.2009.02.022]

Can Hepatocellular Carcinoma tumor grade and microscopical vascular invasion be predicted with an artificial neural network?

Grazi GL;
2009

Abstract

Background and aims. Recurrence after curative treatments of hepatocellular carcinoma on cirrhosis, strongly depends on tumor pathological features such as nuclear grade and microscopic vascular invasion but these data are accurately assessable only on the final surgical specimens. Aim of the present study was to develop an artificial neural network (ANN, a tool showing its greatest strength in case of non linear relationships), able to predict tumor grade and microvascular invasion on the basis of preoperative variables.
2009
Cucchetti A; Piscaglia F; D'Errico A; Ravaioli M; Cescon M; Zanello M; Vivarelli M; Ercolani G; Grazi GL; Golfieri R; Pinna AD
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Utilizza questo identificatore per citare o creare un link a questa risorsa: https://hdl.handle.net/2158/1301408
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