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:

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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2. Global, regional, and national age-sex specific mortality for 264 causes of death;Naghavi;1980–2016: a systematic analysis for the global burden of disease study 2016, The Lancet,2017

3. Optimizing morphology through blood cell image analysis;Merino;Int. J. Lit. Humanit.,2018

4. Retinal vessel segmentation in colour fundus images using extreme learning machine;Zhu;Comput. Med. Imag. Graph.,2017

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