Study of Aided Diagnosis of Hepatic Carcinoma Based on Artificial Neural Network Combined with Tumor Marker Group
| Autor: | Shanjuan Tan, Yongjun Wu, Yiming Wu, Feifei Feng |
|---|---|
| Rok vydání: | 2012 |
| Předmět: |
Artificial neural network
medicine.medical_specialty Receiver operating characteristic biology business.industry Test group Hepatic carcinoma Physics and Astronomy(all) equipment and supplies Linear discriminant analysis Gastroenterology body regions Carcinoembryonic antigen Internal medicine biology.protein Medicine Tumor marker business Aided diagnosis |
| Zdroj: | Physics Procedia. 33:172-178 |
| ISSN: | 1875-3892 |
| Popis: | To develop a computer-aided diagnostic scheme by using an artificial neural network (ANN) combined with tumor markers for diagnosis of hepatic carcinoma (HCC) as a clinical assistant method. 140 serum samples (50 malignant, 40 benign and 50 normal) were analyzed for α-fetoprotein (AFP), carbohydrate antigen 125 (CA125), carcinoembryonic antigen (CEA), sialic acid (SA) and calcium (Ca). The five tumor marker values were then used as ANN inputs data. The result of ANN was compared with that of discriminant analysis by receiver operating characteristic (ROC) curve (AUC) analysis. The diagnostic accuracy of ANN and discriminant analysis among all samples of the test group was 95.5% and 79.3%, respectively. Analysis of multiple tumor markers based on ANN may be a better choice than the traditional statistical methods for differentiating HCC from benign or normal. |
| Databáze: | OpenAIRE |
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