AIMC Topic: Chromosome Aberrations
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Combined molecular subtyping, grading, and segmentation of glioma using multi-task deep learning.
Neuro-oncology
Feb 14, 2023
BACKGROUND: Accurate characterization of glioma is crucial for clinical decision making. A delineation of the tumor is also desirable in the initial decision stages but is time-consuming. Previously, deep learning methods have been developed that can...
Automated classification of cytogenetic abnormalities in hematolymphoid neoplasms.
Bioinformatics (Oxford, England)
Feb 7, 2022
MOTIVATION: Algorithms for classifying chromosomes, like convolutional deep neural networks (CNNs), show promise to augment cytogeneticists' workflows; however, a critical limitation is their inability to accurately classify various structural chromo...
Feasibility Study on Automatic Interpretation of Radiation Dose Using Deep Learning Technique for Dicentric Chromosome Assay.
Radiation research
Feb 1, 2021
The interpretation of radiation dose is an important procedure for both radiological operators and persons who are exposed to background or artificial radiations. Dicentric chromosome assay (DCA) is one of the representative methods of dose estimatio...
THE PROJECT OF ANOTHER LOW-COST METAPHASE FINDER (SECOND REPORT-APPLICATION OF ARTIFICIAL INTELLIGENCE).
Radiation protection dosimetry
Dec 31, 2019
Biological dosimetry is used to estimate individual absorbed radiation dose by quantifying an appropriate biological marker. The most popular gold-standard marker is the appearance of dicentric chromosomes in metaphase. The metaphase finder is a tool...
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