Reliable Probabilistic Prediction for Medical Decision Support
作者： Harris Papadopoulos
DOI: 10.1007/978-3-642-23960-1_32
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摘要: A major drawback of most existing medical decision support systems is that they do not provide any indication about the uncertainty each their predictions. This paper addresses this problem with use a new machine learning framework for producing valid probabilistic predictions, called Venn Prediction (VP). More specifically, VP combined Neural Networks (NNs), which one widely used algorithms. The obtained experimental results on two datasets demonstrate empirically validity outputs and superiority over original NN classifier in terms reliability.
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