AI Medical Compendium Journal:
Cytometry. Part A : the journal of the International Society for Analytical Cytology

Showing 11 to 20 of 62 articles

flowSim: Near duplicate detection for flow cytometry data.

Cytometry. Part A : the journal of the International Society for Analytical Cytology
The analysis of large amounts of data is important for the development of machine learning (ML) models. flowSim is the first algorithm designed to visualize, detect and remove highly redundant information in flow cytometry (FCM) training sets to decr...

Cell damage evaluation by intelligent imaging flow cytometry.

Cytometry. Part A : the journal of the International Society for Analytical Cytology
Essential thrombocythemia (ET) is an uncommon situation in which the body produces too many platelets. This can cause blood clots anywhere in the body and results in various symptoms and even strokes or heart attacks. Removing excessive platelets usi...

Quantification of tumorsphere migration with a physics-based machine learning method.

Cytometry. Part A : the journal of the International Society for Analytical Cytology
Current analysis techniques available for migration assays only provide quantitative measurements for overall migration. However, the potential of regional migration analyses can open further insight into migration patterns and more avenues of experi...

In-silico generation of high-dimensional immune response data in patients using a deep neural network.

Cytometry. Part A : the journal of the International Society for Analytical Cytology
Technologies for single-cell profiling of the immune system have enabled researchers to extract rich interconnected networks of cellular abundance, phenotypical and functional cellular parameters. These studies can power machine learning approaches t...

Sperm-cell DNA fragmentation prediction using label-free quantitative phase imaging and deep learning.

Cytometry. Part A : the journal of the International Society for Analytical Cytology
In intracytoplasmic sperm injection (ICSI), a single sperm cell is selected and injected into an egg. The quality of the chosen sperm and specifically its DNA fragmentation have a significant effect on the fertilization success rate. However, there i...

High-content video flow cytometry with digital cell filtering for label-free cell classification by machine learning.

Cytometry. Part A : the journal of the International Society for Analytical Cytology
Recent development of imaging flow cytometry (IFC) has enabled the measurements of single cells with high throughput, where fluorescent labels provide specificity for cellular diagnosis. The fluorescent labels may disturb the cell functions, and the ...

Classification of peripheral blood neutrophils using deep learning.

Cytometry. Part A : the journal of the International Society for Analytical Cytology
Deep learning has been used to classify the while blood cells in peripheral blood smears. However, the classification of developing neutrophils is rarely studied. Moreover, it is still unknown whether deep learning can work well on the data coming fr...

Toward five-part differential of leukocytes based on electrical impedances of single cells and neural network.

Cytometry. Part A : the journal of the International Society for Analytical Cytology
The five-part differential of leukocytes plays key roles in the diagnosis of a variety of diseases and is realized by optical examinations of single cells, which is prone to various artifacts due to chemical treatments. The classification of leukocyt...

Differentiating single cervical cells by mitochondrial fluorescence imaging and deep learning-based label-free light scattering with multi-modal static cytometry.

Cytometry. Part A : the journal of the International Society for Analytical Cytology
Cervical cancer is a high-risk disease that threatens women's health globally. In this study, we developed the multi-modal static cytometry that adopted different features to classify the typical human cervical epithelial cells (H8) and cervical canc...