Prediction of the early prognosis of the hepatectomized patient with hepatocellular carcinoma with a neural network.
The early prognosis of the hepatectomized patients with hepatocellular carcinoma was determined preoperatively with a perceptron-type neural network. The neural network was trained with the preoperative data of 54 example cases with the early prognosis, successful or died of hepatic dysfunction, as teaching signals. After learning these examples, the neural network came to give a precise prediction to the example data except for one case. With the learned neural network, the outcomes of the hepatectomy of 11 patients (10 successful; 1 died) were predicted prospectively with 100% precision. The usefulness of the neural network for the prediction was determined.
Hamamoto
I
I
First Department of Surgery, Kagawa Medical School, Japan.
Okada
S
S
Hashimoto
T
T
Wakabayashi
H
H
Maeba
T
T
Maeta
H
H
D000328:Adult; D000368:Aged; D006528:Carcinoma, Hepatocellular / Q000000981:diagnostic imaging / Q000601:surgery*; D005260:Female; D005544:Forecasting; D006498:Hepatectomy; D006801:Humans; D007208:Indocyanine Green / Q000378:metabolism; D008099:Liver / Q000378:metabolism; D008113:Liver Neoplasms / Q000000981:diagnostic imaging / Q000601:surgery*; D008297:Male; D008657:Metabolic Clearance Rate; D008875:Middle Aged; D016571:Neural Networks, Computer; D011379:Prognosis; D011446:Prospective Studies; D011856:Radiographic Image Enhancement; D012680:Sensitivity and Specificity; D014057:Tomography, X-Ray Computed; D016896:Treatment Outcome
D007208:Indocyanine Green