A novel method for diagnosing cirrhosis in patients with chronic hepatitis B: artificial neural network approach.
We designed an artificial neural network (ANN) to diagnose cirrhosis in patients with chronic HBV infection. Routine laboratory data (PT, INR, platelet count, direct bilirubin, AST/ALT, AST/PLT) and age were collected from 144 patients. Cirrhosis in these patients was diagnosed by liver biopsy. The ANN's ability was assessed using receiver-operating characteristic (ROC) analysis and the results were compared with a logistic regression model. Our results indicate that the neural network analysis is likely to provide a non-invasive, accurate test for diagnosing cirrhosis in chronic HBV-infected patients, only based on routine laboratory data.
Raoufy
Mohammad Reza
MR
Department of Physiology, School of Medical Sciences, Tarbiat Modares University, Tehran, Iran.
Vahdani
Parviz
P
Alavian
Seyed Moayed
SM
Fekri
Sahba
S
Eftekhari
Parivash
P
Gharibzadeh
Shahriar
S
D000328:Adult; D003430:Cross-Sectional Studies; D005103:Expert Systems; D019694:Hepatitis B, Chronic / Q000150:complications; D006801:Humans; D008103:Liver Cirrhosis / Q000150:complications / Q000175:diagnosis*; D016015:Logistic Models; D008875:Middle Aged; D016571:Neural Networks, Computer; D012372:ROC Curve