کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
495188 862817 2015 8 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Predicting survival of individual patients with esophageal cancer by adaptive neuro-fuzzy inference system approach
ترجمه فارسی عنوان
پیش بینی بقای بیماران فردی مبتلا به سرطان مری با رویکرد سیستم استنتاج فازی سازگار
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر نرم افزارهای علوم کامپیوتر
چکیده انگلیسی


• Based on the adaptive neuro-fuzzy inference system (ANFIS) approach, a hazard modeling and survival prediction system is developed to assist clinicians in prognostic assessment of patients with esophageal cancer and prediction of individual patient survival.
• The results show that application of ANFIS to prognosis prediction for esophageal cancer is a practical and effective method that can predict the survival of patients more accurately.
• This may provide valuable prognostic information in addition to AJCC staging and aid the clinicians’ decision-making process for risk stratification.

Since esophageal cancer has no symptoms in the early stage, it is usually not detected until advanced stages in which treatment is challenging. Integrated treatment provided by a multidisciplinary team is crucial for maximizing the prognosis and survival of patients with esophageal cancer. Currently, clinicians must rely on the cancer staging system for diagnosis and treatment. An accurate and easily applied system for predicting the prognosis of esophageal cancer would be useful for comparing different treatment strategies and for calculating cancer survival probability. This study presents a hazard modeling and survival prediction system based on adaptive neuro-fuzzy inference system (ANFIS) to assist clinicians in prognostic assessment of patients with esophageal cancer and in predicting the survival of individual patients. Expert knowledge was used to construct the fuzzy rule based prognosis inference system for esophageal cancer. Fuzzy logic was used to process the values of input variables rather than categorizing values as normal or abnormal based on cutoffs. After transformation and expansion, censored survival data could be used by the ANFIS for training to establish the risk model for accurately predicting individual survival for different time intervals or for different treatment modalities. Actual values for serum C-reactive protein, albumin, and time intervals were input into the model for use in predicting the survival of individual patients for different time intervals. The curves obtained by the ANFIS approach were fitted to those obtained using the actual values. The comparison results show that the ANFIS is a practical, effective, and accurate method of predicting the survival of esophageal cancer patients.

The survival probability comparisons of the three GPS categories between the predicted results from the ANFIS model (dashed lines) and the Kaplan-Meier estimator results of esophageal cancer (solid lines).Figure optionsDownload as PowerPoint slide

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Applied Soft Computing - Volume 35, October 2015, Pages 583–590
نویسندگان
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