Quantum-inspired Minimum Distance Classification in Biomedical Context. (arXiv:1803.02749v1 [quant-ph])

We face the problem of pattern classification by proposing a quantum-inspired
version of the widely used minimum distance classifier (i.e. the Nearest Mean
Classifier (NMC)) already introduced in [31,33,28,27] and by applying this
quantum-inspired classifier in a biomedical context. In particular, we show and
compare the NMC and our quantum model performance to solve a problem related to
classify the probability of survival for patients affected by idiopathic
pulmonary fibrosis (IPF).

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