A semi-supervised method for predicting cancer survival using incomplete clinical data

@article{Hassanzadeh2015ASM,
  title={A semi-supervised method for predicting cancer survival using incomplete clinical data},
  author={Hamid Reza Hassanzadeh and John H. Phan and May D. Wang},
  journal={2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)},
  year={2015},
  pages={210-213}
}
Prediction of survival for cancer patients is an open area of research. However, many of these studies focus on datasets with a large number of patients. We present a novel method that is specifically designed to address the challenge of data scarcity, which is often the case for cancer datasets. Our method is able to use unlabeled data to improve classification by adopting a semi-supervised training approach to learn an ensemble classifier. The results of applying our method to three cancer… CONTINUE READING
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