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Computational Study of Methods for Determining the Elasticity of Red Blood Cells Using Machine Learning.
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- Symmetry (20738994), 2022, v. 14, n. 8, p. 1732, doi. 10.3390/sym14081732
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Classification of Red Blood Cell Rigidity from Sequence Data of Blood Flow Simulations Using Neural Networks.
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- Symmetry (20738994), 2021, v. 13, n. 6, p. 938, doi. 10.3390/sym13060938
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Markov-Modulated On–Off Processes in IP Traffic Modeling.
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- Mathematics (2227-7390), 2023, v. 11, n. 14, p. 3089, doi. 10.3390/math11143089
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Applications of machine learning for simulations of red blood cells in microfluidic devices.
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- BMC Bioinformatics, 2020, v. 21, p. 1, doi. 10.1186/s12859-020-3357-5
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Comparative Study of Computational Methods for Classifying Red Blood Cell Elasticity.
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- Applied Sciences (2076-3417), 2024, v. 14, n. 20, p. 9315, doi. 10.3390/app14209315
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Classification of Red Blood Cells Using Time-Distributed Convolutional Neural Networks from Simulated Videos.
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- Applied Sciences (2076-3417), 2023, v. 13, n. 13, p. 7967, doi. 10.3390/app13137967
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- Article
High-Resolution Breakpoint Analysis Provides Evidence for the Sequence-Directed Nature of Genome Rearrangements in Hereditary Disorders.
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- Human Mutation, 2015, v. 36, n. 2, p. 250, doi. 10.1002/humu.22734
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- Article