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Deep Learning Models for Classification of Red Blood Cells in Microscopy Images to Aid in Sickle Cell Anemia Diagnosis

机译：深度学习模型，用于分类显微镜图像中的红细胞，以帮助镰状细胞贫血诊断

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Laith Alzubaidi; Mohammed A. Fadhel; Omran Al-Shamma; Jinglan Zhang; Ye Duan;
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年度 2020
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1. Diagnosis support of sickle cell anemia by classifying red blood cell shape in peripheral blood images [J] . Medical and Biological Engineering and Computing: Journal of the International Federation for Medical and Biological Engineering . 2020,第6期

机译：通过在外周血图像中分类红细胞形状来诊断镰状细胞贫血
2. A deep convolutional neural network for classification of red blood cells in sickle cell anemia [J] . Mengjia Xu, Dimitrios P. Papageorgiou, Sabia Z. Abidi, PLoS Computational Biology . 2017,第10期

机译：用于镰状细胞性贫血中红细胞分类的深度卷积神经网络
3. Integrating deep learning with microfluidics for biophysical classification of sickle red blood cells adhered to laminin [J] . Niksa PraljakID, Shamreen IramID, Utku GorekeID, PLoS Computational Biology . 2021,第11期

机译：与微流体集成深度学习，为粘附到层内的镰刀红细胞生物物理分类
4. Classification of Red Blood Cells in Sickle Cell Anemia Using Deep Convolutional Neural Network [C] . Laith Alzubaidi, Omran Al-Shamma, Mohammed A. Fadhel, International Conference on Intelligent Systems Design and Applications . 2020

机译：深卷积神经网络镰状细胞贫血红细胞的分类
5. Modeling of sickle cell anemia utilizing disease-specific induced pluripotent stem cells. [D] . Rozelle, Sarah Sundstrom. 2014

机译：利用疾病特异性诱导的多能干细胞对镰状细胞贫血进行建模。
6. DeepQuantify: deep learning and quantification system of white blood cells in light microscopy images of injured skeletal muscles [O] . Yang Jiao, Barbara St. Pierre Schneider, Emma Regentova, 2019

机译：DeepQuantify：损伤骨骼肌的光学显微镜图像中白细胞的深度学习和定量系统
7. A deep learning AlexNet model for classification of red blood cells in sickle cell anemia [O] . Hajara Aliyu Abdulkarim, Mohd Azhar Abdul Razak, Rubita Sudirman, 2020

机译：一种深入学习镰状细胞贫血中红细胞分类的亚历纳克特模型

Deep Learning Models for Classification of Red Blood Cells in Microscopy Images to Aid in Sickle Cell Anemia Diagnosis

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