Statistical Model to Determine the Factors that Affect Liver Cancer
| المصدر: | المجلة العلمية للاقتصاد والتجارة |
|---|---|
| الناشر: | جامعة عين شمس - كلية التجارة |
| المؤلف الرئيسي: | Aziz, Merna Atef Shafeek (Author) |
| مؤلفين آخرين: | Abdel Aal, Medhat Mohamed Ahmed (Advisor) |
| المجلد/العدد: | ع3 |
| محكمة: | نعم |
| الدولة: |
مصر |
| التاريخ الميلادي: |
2016
|
| الشهر: | يوليو |
| الصفحات: | 79 - 95 |
| ISSN: |
2636-2562 |
| رقم MD: | 810787 |
| نوع المحتوى: | بحوث ومقالات |
| اللغة: | الإنجليزية |
| قواعد المعلومات: | EcoLink |
| مواضيع: | |
| كلمات المؤلف المفتاحية: |
Primary Liver Cancer | Hepatocellular Carcinoma | Hepatitis C Virus | Discriminant Analysis | Logistic Regression Analysis | Artificial Neural Networks | Classification and Regression Tree
|
| رابط المحتوى: |
عدد مرات التحميل
23
| المستخلص: |
This study aims to identify the risk factors that affect the survival of liver cancer (hepatocellular carcinoma) patients, using the statistical models to estimate the probability of survival of hepatocellular carcinoma (HCC) patients, especially in the light of spread of hepatitis C virus infection, and its impact on the probability of a decline in survival of these patients. Some of the risk factors such as hepatitis C virus, patient’s age group, patient’s gender, alpha fetoprotein (AFP), Performance Status (PS), and Child Score has been studied in this study using discriminant analysis model, logistic regression mode, artificial neural networks model, and classification and regression tree model for prediction of survival of hepatocellular carcinoma patients, and concluded that the discriminant analysis model, logistic regression model, artificial neural network analysis focusing on multilayer perceptron network algorithms, and classification and regression tree model, showed that hepatitis C virus variable, age groups variable, Child Score variable, Alpha fetoprotein variable are risk factors that affect the decrease in survival of HCC patients. |
|---|---|
| ISSN: |
2636-2562 |
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