Sickle-cell disease diagnosis support selecting the most appropriate machine learning method: Towards a general and interpretable approach for cell morphology analysis from microscopy images

Natasa Petrovic, Gabriel Moyà Alcover, Antoni Jaume-i-Capó, Manuel González Hidalgo. Sickle-cell disease diagnosis support selecting the most appropriate machine learning method: Towards a general and interpretable approach for cell morphology analysis from microscopy images. Comp. in Bio. and Med., 126:104027, 2020. [doi]

@article{PetrovicMJH20,
  title = {Sickle-cell disease diagnosis support selecting the most appropriate machine learning method: Towards a general and interpretable approach for cell morphology analysis from microscopy images},
  author = {Natasa Petrovic and Gabriel Moyà Alcover and Antoni Jaume-i-Capó and Manuel González Hidalgo},
  year = {2020},
  doi = {10.1016/j.compbiomed.2020.104027},
  url = {https://doi.org/10.1016/j.compbiomed.2020.104027},
  researchr = {https://researchr.org/publication/PetrovicMJH20},
  cites = {0},
  citedby = {0},
  journal = {Comp. in Bio. and Med.},
  volume = {126},
  pages = {104027},
}