Search alternatives:
feature optimization » resource optimization (Expand Search), feature elimination (Expand Search), structure optimization (Expand Search)
primary cell » primary cells (Expand Search), primary cilia (Expand Search), primary care (Expand Search)
cell feature » cell features (Expand Search), all feature (Expand Search), scale feature (Expand Search)
feature optimization » resource optimization (Expand Search), feature elimination (Expand Search), structure optimization (Expand Search)
primary cell » primary cells (Expand Search), primary cilia (Expand Search), primary care (Expand Search)
cell feature » cell features (Expand Search), all feature (Expand Search), scale feature (Expand Search)
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Label-Free Assessment of the Drug Resistance of Epithelial Ovarian Cancer Cells in a Microfluidic Holographic Flow Cytometer Boosted through Machine Learning
Published 2021“…Several morphologic and texture features at a single-cell level have been extracted from the quantitative phase images. …”
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Label-Free Assessment of the Drug Resistance of Epithelial Ovarian Cancer Cells in a Microfluidic Holographic Flow Cytometer Boosted through Machine Learning
Published 2021“…Several morphologic and texture features at a single-cell level have been extracted from the quantitative phase images. …”
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Table1_Identification of biomarkers for hepatocellular carcinoma based on single cell sequencing and machine learning algorithms.DOCX
Published 2022“…In this study, based on the scRNA-seq results of primary neoplastic cells and paired normal liver cells from eight HCC patients, a new strategy of machine learning algorithms was applied to screen core biomarkers that distinguished HCC tumor tissues from the adjacent normal liver. …”
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Trace, Machine Learning of Signal Images for Trace-Sensitive Mass Spectrometry: A Case Study from Single-Cell Metabolomics
Published 2019“…Recent developments in high-resolution mass spectrometry (HRMS) technology enabled ultrasensitive detection of proteins, peptides, and metabolites in limited amounts of samples, even single cells. However, extraction of trace-abundance signals from complex data sets (<i>m</i>/<i>z</i> value, separation time, signal abundance) that result from ultrasensitive studies requires improved data processing algorithms. …”
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Trace, Machine Learning of Signal Images for Trace-Sensitive Mass Spectrometry: A Case Study from Single-Cell Metabolomics
Published 2019“…Recent developments in high-resolution mass spectrometry (HRMS) technology enabled ultrasensitive detection of proteins, peptides, and metabolites in limited amounts of samples, even single cells. However, extraction of trace-abundance signals from complex data sets (<i>m</i>/<i>z</i> value, separation time, signal abundance) that result from ultrasensitive studies requires improved data processing algorithms. …”
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Proposed model tuned hyperparameters.
Published 2024“…To select the most informative features for effective segmentation, we utilize an advanced meta-heuristics algorithm called Advanced Whale Optimization (AWO). …”
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The workflow of the proposed model.
Published 2024“…To select the most informative features for effective segmentation, we utilize an advanced meta-heuristics algorithm called Advanced Whale Optimization (AWO). …”
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ResNeXt101 training and results.
Published 2024“…To select the most informative features for effective segmentation, we utilize an advanced meta-heuristics algorithm called Advanced Whale Optimization (AWO). …”
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Proposed model specificity and DSC outcomes.
Published 2024“…To select the most informative features for effective segmentation, we utilize an advanced meta-heuristics algorithm called Advanced Whale Optimization (AWO). …”
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Accuracy comparison of proposed and other models.
Published 2024“…To select the most informative features for effective segmentation, we utilize an advanced meta-heuristics algorithm called Advanced Whale Optimization (AWO). …”
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Architecture of ConvNet.
Published 2024“…To select the most informative features for effective segmentation, we utilize an advanced meta-heuristics algorithm called Advanced Whale Optimization (AWO). …”
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Comparison of state-of-the-art method.
Published 2024“…To select the most informative features for effective segmentation, we utilize an advanced meta-heuristics algorithm called Advanced Whale Optimization (AWO). …”
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Proposed model sensitivity outcome.
Published 2024“…To select the most informative features for effective segmentation, we utilize an advanced meta-heuristics algorithm called Advanced Whale Optimization (AWO). …”
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Proposed ResNeXt101 operational flow.
Published 2024“…To select the most informative features for effective segmentation, we utilize an advanced meta-heuristics algorithm called Advanced Whale Optimization (AWO). …”
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