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arXiv · 1803.02749

Quantum-inspired Minimum Distance Classification in Biomedical Context

Giuseppe Sergioli·Giorgio Russo·Enrica Santucci·Alessandro Stefano·Sebastiano Emanuele Torrisi·Stefano Palmucci·Carlo Vancheri·Roberto Giuntini
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Abstract

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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Giuseppe Sergioli, Giorgio Russo, Enrica Santucci, Alessandro Stefano, Sebastiano Emanuele Torrisi, Stefano Palmucci, Carlo Vancheri, Roberto Giuntini. 2018-03-07. Quantum-inspired Minimum Distance Classification in Biomedical Context. https://arxiv.org/abs/1803.02749

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