Flow Cytometry-Based Classification in Cancer Research: A View on Feature Selection.

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Improving Gastric Cancer Outcome Prediction Using Single Time-Point Artificial Neural Network Models.

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Flow Cytometry-Based Classification in Cancer Research: A View on Feature Selection.

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Flow Cytometry-Based Classification in Cancer Research: A View on Feature Selection.

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Flow Cytometry-Based Classification in Cancer Research: A View on Feature Selection.

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Flow Cytometry-Based Classification in Cancer Research: A View on Feature Selection.

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Flow Cytometry-Based Classification in Cancer Research: A View on Feature Selection.

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Flow Cytometry-Based Classification in Cancer Research: A View on Feature Selection.

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Flow Cytometry-Based Classification in Cancer Research: A View on Feature Selection.

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Flow Cytometry-Based Classification in Cancer Research: A View on Feature Selection

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P2093

Pekka Ruusuvuori

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Single-cell mass cytometry of differential immune and drug responses across a human hematopoietic continuum

Regularization Paths for Generalized Linear Models via Coordinate Descent

Critical assessment of automated flow cytometry data analysis techniques.

Analysis of flow cytometry data by matrix relevance learning vector quantization

Sparse inverse covariance estimation with the graphical lasso.

Cytometric fingerprinting: quantitative characterization of multivariate distributions.

Leukemia prediction using sparse logistic regression.

Epigenetically altered miR-193b targets cyclin D1 in prostate cancer

Recent advances in flow cytometry: application to the diagnosis of hematologic malignancy.

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75-85

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scholarly article

P356

10.4137/CIN.S30795

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Suppl 5

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Leena Latonen

Heikki Huttunen

S Sakira Hassan

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2015-01-01T00:00:00Z

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27081305

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4827794

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Flow Cytometry-Based Classification in Cancer Research: A View on Feature Selection.

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P2860

P2860

Flow Cytometry-Based Classification in Cancer Research: A View on Feature Selection.

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