Quantum-inspired Minimum Distance Classification in Biomedical Context
Quantum Physics
2018-03-08 v1
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).
Cite
@article{arxiv.1803.02749,
title = {Quantum-inspired Minimum Distance Classification in Biomedical Context},
author = {Giuseppe Sergioli and Giorgio Russo and Enrica Santucci and Alessandro Stefano and Sebastiano Emanuele Torrisi and Stefano Palmucci and Carlo Vancheri and Roberto Giuntini},
journal= {arXiv preprint arXiv:1803.02749},
year = {2018}
}