Survival Risk Prediction of Esophageal Cancer Based on Self-Organizing Maps Clustering and Support Vector Machine Ensembles
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DOI: 10.1109/access.2020.3007785
Abstract: This article provides a method based on self-organizing maps (SOM) neural network clustering and support vector machine (SVM) ensembles to predict the survival risk levels of esophageal cancer. Nine blood indexes related to patient survival… read more here.
Keywords: organizing maps; risk; based self; prediction ... See more keywords