Improving prognosis and reducing decision regret for pancreatic cancer treatment using artificial neural networks
作者:
Highlights:
• ANN developed to predict 7-month survival of pancreatic cancer patients.
• ANN achieves 91.30% sensitivity, 38.27% specificity, and overall accuracy of 71.69%.
• The ANN performs at least as well as Cox-regression and outperforms Cox-regression on specificity.
• Treatment decision regret may be reduced for physicians and patients when using the ANN's survival predictions.
摘要
Cancer is a worldwide health problem with extremely high morbidity and mortality. Pancreatic cancer specifically is the fourth leading cause of death by cancer in the United States and is a leading cause of cancer deaths worldwide. The optimal treatment for pancreatic cancer is resection surgery, but even with surgery many patients suffer high morbidity and mortality, leading to regret in physicians over whether or not the optimal course of treatment with regard to the patient's quality of life was made. Patients also suffer regret concerning the morbidity associated with treatment. An artificial neural network is developed to predict 7-month survival of pancreatic cancer patients that achieves over a 91% sensitivity and an overall accuracy above 70%. The artificial neural network outcome predictions may be used as an additional source of information to assist physicians and patients in selecting the treatment that provides the best quality of life for the patient and reduces treatment decision regret.
论文关键词:Artificial neural network,Cancer,Pancreas,Regret reduction,Survival
论文评审过程:Received 17 August 2017, Revised 12 December 2017, Accepted 12 December 2017, Available online 16 December 2017, Version of Record 12 January 2018.
论文官网地址:https://doi.org/10.1016/j.dss.2017.12.007