AIMC Topic: Lymphocytes

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Tens of images can suffice to train neural networks for malignant leukocyte detection.

Scientific reports
Convolutional neural networks (CNNs) excel as powerful tools for biomedical image classification. It is commonly assumed that training CNNs requires large amounts of annotated data. This is a bottleneck in many medical applications where annotation r...

Correlation between lung infection severity and clinical laboratory indicators in patients with COVID-19: a cross-sectional study based on machine learning.

BMC infectious diseases
BACKGROUND: Coronavirus disease 2019 (COVID-19) has caused a global pandemic that has raised worldwide concern. This study aims to investigate the correlation between the extent of lung infection and relevant clinical laboratory testing indicators in...

Comparison of MPL-ANN and PLS-DA models for predicting the severity of patients with acute pancreatitis: An exploratory study.

The American journal of emergency medicine
OBJECTIVE: Acute pancreatitis (AP) is a common inflammatory disorder that may develop into severe AP (SAP), resulting in life-threatening complications and even death. The purpose of this study was to explore two different machine learning models of ...

A rapid white blood cell classification system based on multimode imaging technology.

Journal of biophotonics
In order to simplify the complexity of white blood cell classification in existing point-of-care testing (POCT) testing equipment, a white blood cell classification detection system based on microfluidic and multimode imaging was constructed. Microfl...

Improved Classification of White Blood Cells with the Generative Adversarial Network and Deep Convolutional Neural Network.

Computational intelligence and neuroscience
White blood cells (leukocytes) are a very important component of the blood that forms the immune system, which is responsible for fighting foreign elements. The five types of white blood cells include , , , , and , where each type constitutes a diffe...

Purification of viable peripheral blood mononuclear cells for biobanking using a robotized liquid handling workstation.

Journal of translational medicine
BACKGROUND: The purification of peripheral blood mononuclear cells (PBMCs) by means of density gradient (1.07 g/mL) centrifugation is one of the most commonly used methods in diagnostics and research laboratories as well as in biobanks. Here, we eval...

Classification of DNA damages on segmented comet assay images using convolutional neural network.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Identification and quantification of DNA damage is a very significant subject in biomedical research area which still needs more robust and effective methods. One of the cheapest, easy to use and most successful method for D...

White blood cells detection and classification based on regional convolutional neural networks.

Medical hypotheses
White blood cells (WBC) are important parts of our immune system and they protect our body against infections by eliminating viruses, bacteria, parasites and fungi. There are five types of WBC. These are called Lymphocytes, Monocytes, Eosinophils, Ba...

Learning to detect lymphocytes in immunohistochemistry with deep learning.

Medical image analysis
The immune system is of critical importance in the development of cancer. The evasion of destruction by the immune system is one of the emerging hallmarks of cancer. We have built a dataset of 171,166 manually annotated CD3 and CD8 cells, which we us...