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-Reference-Cited by-同舟云学术

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

Published:2020-11 Issue: Volume:126 Page:104027
ISSN:0010-4825
Container-title:Computers in Biology and Medicine
language:en
Short-container-title:Computers in Biology and Medicine

Author:

Petrović Nataša,Moyà-Alcover Gabriel,Jaume-i-Capó Antoni,González-Hidalgo Manuel

Funder

Project EXPLainable Artificial INtelligence systems for health and well-beING

Publisher

Elsevier BV

Subject

Health Informatics,Computer Science Applications

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