Artificial neural networks (ANNs) are nonlinear pattern recognition techniques that can be used as a tool in medical decision making. The objective of this study was to develop an ANN model for predicting survival in patients with pancreatic ductal adenocarcinoma (PDAC)
Background. Early and accurate evaluation of severity and prognosis in acute pancreatitis (AP), espe...
IntroductionPancreatic ductal adenocarcinoma (PDAC) is an aggressive malignancy with a poor prognosi...
Abstract Background Cox proportional hazard model (CPH) is commonly used in clinical research for s...
BACKGROUND: An artificial neural network (ANNs) is a non-linear pattern recognition technique that i...
The analysis of cancer survival is used to determine the efficiency of treatment programmes and prot...
Prediction of long-term survival in patients with invasive intraductal papillary mucinous neoplasm (...
Cancer survival prediction in patients who had undergone surgical intervention is an important step...
OBJECTIVE: To construct an artificial neural network (ANN) model to predict survival after liver res...
In cancer studies, the prediction of cancer outcome based on a set of prognostic variables has been ...
Predicting the probable survival for a patient can be very challenging for many diseases. In many fo...
[[abstract]]This study created a survival prediction model for liver cancer using data mining algori...
[[abstract]]This study created a survival prediction model for liver cancer using data mining algori...
[[abstract]]This study created a survival prediction model for liver cancer using data mining algori...
Artificial neural networks (ANNs) is a nonlinear pattern recognition technique inspired by the funct...
Abstract ANNs are nonlinear regression computational devices that have been used for over 45 years i...
Background. Early and accurate evaluation of severity and prognosis in acute pancreatitis (AP), espe...
IntroductionPancreatic ductal adenocarcinoma (PDAC) is an aggressive malignancy with a poor prognosi...
Abstract Background Cox proportional hazard model (CPH) is commonly used in clinical research for s...
BACKGROUND: An artificial neural network (ANNs) is a non-linear pattern recognition technique that i...
The analysis of cancer survival is used to determine the efficiency of treatment programmes and prot...
Prediction of long-term survival in patients with invasive intraductal papillary mucinous neoplasm (...
Cancer survival prediction in patients who had undergone surgical intervention is an important step...
OBJECTIVE: To construct an artificial neural network (ANN) model to predict survival after liver res...
In cancer studies, the prediction of cancer outcome based on a set of prognostic variables has been ...
Predicting the probable survival for a patient can be very challenging for many diseases. In many fo...
[[abstract]]This study created a survival prediction model for liver cancer using data mining algori...
[[abstract]]This study created a survival prediction model for liver cancer using data mining algori...
[[abstract]]This study created a survival prediction model for liver cancer using data mining algori...
Artificial neural networks (ANNs) is a nonlinear pattern recognition technique inspired by the funct...
Abstract ANNs are nonlinear regression computational devices that have been used for over 45 years i...
Background. Early and accurate evaluation of severity and prognosis in acute pancreatitis (AP), espe...
IntroductionPancreatic ductal adenocarcinoma (PDAC) is an aggressive malignancy with a poor prognosi...
Abstract Background Cox proportional hazard model (CPH) is commonly used in clinical research for s...
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