AIMC Topic: Erythrocytes

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Single Cell Analysis of Stored Red Blood Cells Using Ultra-High Throughput Holographic Cytometry.

Cells Sep 17, 2021
Holographic cytometry is introduced as an ultra-high throughput implementation of quantitative phase imaging of single cells flowing through parallel microfluidic channels. Here, the approach was applied for characterizing the morphology of individua...
Machine Learning Algorithms Humans Flow Cytometry Erythrocytes Holography Single-Cell Analysis Image Processing, Computer-Assisted
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Cell Mechanics Based Computational Classification of Red Blood Cells Via Machine Intelligence Applied to Morpho-Rheological Markers.

IEEE/ACM transactions on computational biology and bioinformatics Aug 6, 2021
Despite fluorescent cell-labelling being widely employed in biomedical studies, some of its drawbacks are inevitable, with unsuitable fluorescent probes or probes inducing a functional change being the main limitations. Consequently, the demand for a...
Reticulocytes Computational Biology Unsupervised Machine Learning Erythrocytes Image Cytometry Rheology Humans Biomarkers
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Automatic identification of malaria and other red blood cell inclusions using convolutional neural networks.

Computers in biology and medicine Jul 22, 2021
Malaria is a serious disease responsible for thousands of deaths each year. Many efforts have been made to aid in the diagnosis of malaria using machine learning techniques, but to date, the presence of other elements that may interfere with the reco...
Humans Neural Networks, Computer Malaria Erythrocytes
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Combining microfluidics with machine learning algorithms for RBC classification in rare hereditary hemolytic anemia.

Scientific reports Jun 30, 2021
Combining microfluidics technology with machine learning represents an innovative approach to conduct massive quantitative cell behavior study and implement smart decision-making systems in support of clinical diagnostics. The spleen plays a key-role...
Erythrocytes Lab-On-A-Chip Devices Male Image Processing, Computer-Assisted Anemia, Hemolytic, Congenital Microfluidic Analytical Techniques Erythrocyte Deformability Machine Learning Female Humans
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Machine learning for predicting preoperative red blood cell demand.

Transfusion medicine (Oxford, England) May 24, 2021
BACKGROUND: The paucity of accurate quantitative standards for determining the quantity of red blood cells (RBCs) needed for perioperative patients and the predominant application of the "preoperative hemoglobin + surgery type" empirical decision-mak...
Blood Transfusion Erythrocytes Machine Learning Retrospective Studies Humans Artificial Intelligence
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Red blood cell phenotyping from 3D confocal images using artificial neural networks.

PLoS computational biology May 13, 2021
The investigation of cell shapes mostly relies on the manual classification of 2D images, causing a subjective and time consuming evaluation based on a portion of the cell surface. We present a dual-stage neural network architecture for analyzing fin...
Humans Neural Networks, Computer Case-Control Studies Image Processing, Computer-Assisted Reproducibility of Results Automation Microscopy, Confocal Erythrocytes
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Clustering-Based Dual Deep Learning Architecture for Detecting Red Blood Cells in Malaria Diagnostic Smears.

IEEE journal of biomedical and health informatics May 11, 2021
Computer-assisted algorithms have become a mainstay of biomedical applications to improve accuracy and reproducibility of repetitive tasks like manual segmentation and annotation. We propose a novel pipeline for red blood cell detection and counting ...
Malaria Erythrocytes Image Processing, Computer-Assisted Cluster Analysis Reproducibility of Results Humans Deep Learning
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Detecting cells rotations for increasing the robustness of cell sizing by impedance measurements, with or without machine learning.

Cytometry. Part A : the journal of the International Society for Analytical Cytology May 7, 2021
The Coulter principle is a widespread technique for sizing red blood cells (RBCs) in hematological analyzers. It is based on the monitoring of the electrical perturbations generated by cells passing through a micro-orifice, in which a concentrated el...
Electrodes Electric Impedance Machine Learning Cell Size Erythrocytes
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Emerging use of machine learning and advanced technologies to assess red cell quality.

Transfusion and apheresis science : official journal of the World Apheresis Association : official journal of the European Society for Haemapheresis Nov 21, 2020
Improving blood product quality and patient outcomes is an accepted goal in transfusion medicine research. Thus, there is an urgent need to understand the potential adverse effects on red blood cells (RBCs) during pre-transfusion storage. Current ass...
Humans Artificial Intelligence Erythrocytes Machine Learning Flow Cytometry
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Machine learning assistive rapid, label-free molecular phenotyping of blood with two-dimensional NMR correlational spectroscopy.

Communications biology Sep 28, 2020
Translation of the findings in basic science and clinical research into routine practice is hampered by large variations in human phenotype. Developments in genotyping and phenotyping, such as proteomics and lipidomics, are beginning to address these...
Magnetic Resonance Spectroscopy Blood Proteins Point-of-Care Testing Erythrocytes Oxygen Blood Machine Learning Hemoglobins Blood Chemical Analysis Phenotype
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