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"Sickle-cell disease diagnosis support selecting the most appropriate ..."

Natasa Petrovic et al. (2020)

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DOI: —

access: open

type: Informal or Other Publication

metadata version: 2020-10-13

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  - electronic edition @ arxiv.org (open access)
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  dblp key:
  - journals/corr/abs-2010-04511
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  persistent URL:
  - https://dblp.org/rec/journals/corr/abs-2010-04511
Natasa Petrovic, Gabriel Moyà-Alcover, Antoni Jaume-i-Capó, Manuel González Hidalgo:
Sickle-cell disease diagnosis support selecting the most appropriate machinelearning method: Towards a general and interpretable approach for cellmorphology analysis from microscopy images. CoRR abs/2010.04511 (2020)

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