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Full-Text Articles in Laboratory Medicine
Distinguishing Leukemic Cells Using Fractal Chromatin Patterns And Machine Learning, Abigail Gordhamer, Paul Young, Ryan Cordner
Distinguishing Leukemic Cells Using Fractal Chromatin Patterns And Machine Learning, Abigail Gordhamer, Paul Young, Ryan Cordner
Annual Research Symposium
One of the most important tests in the clinical laboratory is the Complete Blood Count, which involves identifying the white blood cells in a patient’s blood. The respective counts of the different white blood cell types correlate with various states of health and disease, and are critical to diagnosing diseases such as leukemia. Leukemic cells are considered especially difficult to distinguish, and it is of the upmost importance that these cells are identified correctly. To aid in the process of leukemic cell identification, we quantified fractal patterns in the chromatin of white blood cells and used the data to identify …
Chromatin Pattern Quantification For The Differentiation Of White Blood Cells, Paul Young, Ryan Cordner, Abigail Gordhamer
Chromatin Pattern Quantification For The Differentiation Of White Blood Cells, Paul Young, Ryan Cordner, Abigail Gordhamer
Annual Research Symposium
Nuclear chromatin patterns have been used historically to distinguish between different developmental stages and lineages of white blood cells. While it is common to characterize cells based on arbitrary ‘open’ or ‘closed’ chromatin patterns, quantification of chromatin data is lacking. By extracting nuclei from a database of white blood cells and running fractal analyses using TWOMBLI, we were able to produce meaningful data quantifying chromatin patterns. Our data were put through a random forest algorithm which grouped each point based on relationship probability. The algorithm compared immature and mature cell types as well as cells of similar maturity and differing …