Comparative analysis of cell parameter groups for breast cancer detection

David Blokh; Ilia Stambler; Elena Afrimzon; Max Platkov; Yana Shafran; Eden Korech; Judith Sandbank; Naomi Zurgil; Mordechai Deutsch

doi:10.1016/j.cmpb.2009.01.005

Comparative analysis of cell parameter groups for breast cancer detection

David Blokh, Ilia Stambler, Elena Afrimzon, Max Platkov, Yana Shafran, Eden Korech, Judith Sandbank, Naomi Zurgil, Mordechai Deutsch

Research output: Contribution to journal › Article › peer-review

6 Scopus citations

Abstract

We present a method for the comparative analysis of parameter groups according to their correlation to disease. The theoretical basis of the proposed method is Information Theory and Nonparametric Statistics. Normalized mutual information is used as the measure of correlation between parameters, and statistical conclusions are based on ranking. The fluorescence polarization (FP) parameter is considered as the principal diagnostic characteristic. The FP was measured in fluorescein diacetate (FDA)-stained individual peripheral blood mononuclear cells (PBMC), derived from healthy subjects and breast cancer (BC) patients, under different stimulation conditions: by tumor tissue, the mitogen phytohemagglutinin (PHA) or without the stimulants. The FP parameters were grouped according to their correlation with breast cancer. It was established that the greatest difference between cells of BC patients and healthy subjects is found in the PHA test (parameter P1).

Original language	English
Pages (from-to)	239-249
Number of pages	11
Journal	Computer Methods and Programs in Biomedicine
Volume	94
Issue number	3
DOIs	https://doi.org/10.1016/j.cmpb.2009.01.005
State	Published - Jun 2009

Bibliographical note

Funding Information:
This research was supported by The Komen Foundation, The Horowitz Foundation and by US Army Medical Research and Material Command Grant DAMD17-01-1-0131.

Keywords

Breast cancer (BC)
Fluorescence polarization (FP)
Information Theory
Mitogenic stimulation
Nonparametric Statistics
Peripheral blood mononuclear cells (PBMC)
Selecting parameter groups

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This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.1016/j.cmpb.2009.01.005

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title = "Comparative analysis of cell parameter groups for breast cancer detection",

abstract = "We present a method for the comparative analysis of parameter groups according to their correlation to disease. The theoretical basis of the proposed method is Information Theory and Nonparametric Statistics. Normalized mutual information is used as the measure of correlation between parameters, and statistical conclusions are based on ranking. The fluorescence polarization (FP) parameter is considered as the principal diagnostic characteristic. The FP was measured in fluorescein diacetate (FDA)-stained individual peripheral blood mononuclear cells (PBMC), derived from healthy subjects and breast cancer (BC) patients, under different stimulation conditions: by tumor tissue, the mitogen phytohemagglutinin (PHA) or without the stimulants. The FP parameters were grouped according to their correlation with breast cancer. It was established that the greatest difference between cells of BC patients and healthy subjects is found in the PHA test (parameter P1).",

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author = "David Blokh and Ilia Stambler and Elena Afrimzon and Max Platkov and Yana Shafran and Eden Korech and Judith Sandbank and Naomi Zurgil and Mordechai Deutsch",

note = "Funding Information: This research was supported by The Komen Foundation, The Horowitz Foundation and by US Army Medical Research and Material Command Grant DAMD17-01-1-0131.",

year = "2009",

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doi = "10.1016/j.cmpb.2009.01.005",

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AU - Blokh, David

AU - Stambler, Ilia

AU - Afrimzon, Elena

AU - Platkov, Max

AU - Shafran, Yana

AU - Korech, Eden

AU - Sandbank, Judith

AU - Zurgil, Naomi

AU - Deutsch, Mordechai

N1 - Funding Information: This research was supported by The Komen Foundation, The Horowitz Foundation and by US Army Medical Research and Material Command Grant DAMD17-01-1-0131.

PY - 2009/6

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N2 - We present a method for the comparative analysis of parameter groups according to their correlation to disease. The theoretical basis of the proposed method is Information Theory and Nonparametric Statistics. Normalized mutual information is used as the measure of correlation between parameters, and statistical conclusions are based on ranking. The fluorescence polarization (FP) parameter is considered as the principal diagnostic characteristic. The FP was measured in fluorescein diacetate (FDA)-stained individual peripheral blood mononuclear cells (PBMC), derived from healthy subjects and breast cancer (BC) patients, under different stimulation conditions: by tumor tissue, the mitogen phytohemagglutinin (PHA) or without the stimulants. The FP parameters were grouped according to their correlation with breast cancer. It was established that the greatest difference between cells of BC patients and healthy subjects is found in the PHA test (parameter P1).

AB - We present a method for the comparative analysis of parameter groups according to their correlation to disease. The theoretical basis of the proposed method is Information Theory and Nonparametric Statistics. Normalized mutual information is used as the measure of correlation between parameters, and statistical conclusions are based on ranking. The fluorescence polarization (FP) parameter is considered as the principal diagnostic characteristic. The FP was measured in fluorescein diacetate (FDA)-stained individual peripheral blood mononuclear cells (PBMC), derived from healthy subjects and breast cancer (BC) patients, under different stimulation conditions: by tumor tissue, the mitogen phytohemagglutinin (PHA) or without the stimulants. The FP parameters were grouped according to their correlation with breast cancer. It was established that the greatest difference between cells of BC patients and healthy subjects is found in the PHA test (parameter P1).

KW - Breast cancer (BC)

KW - Fluorescence polarization (FP)

KW - Information Theory

KW - Mitogenic stimulation

KW - Nonparametric Statistics

KW - Peripheral blood mononuclear cells (PBMC)

KW - Selecting parameter groups

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ER -

Comparative analysis of cell parameter groups for breast cancer detection

Abstract

Bibliographical note

Keywords

UN SDGs

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