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Comparison of Mathematical Models for Radiation Fractionation
by
McLarty, Jerry W.
, Hethcote, Herbert W.
, Thames, Howard D.
in
Cell Survival - radiation effects
/ Dose fractionation
/ Dose response relationship
/ Dose-Response Relationship, Radiation
/ Fractionation
/ Geometric planes
/ Linear regression
/ Mathematical models
/ Mathematics
/ Models, Biological
/ Parametric models
/ Radiation dosage
/ Radiation dose response relationship
/ Radiotherapy
/ Radiotherapy Dosage
1976
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Comparison of Mathematical Models for Radiation Fractionation
by
McLarty, Jerry W.
, Hethcote, Herbert W.
, Thames, Howard D.
in
Cell Survival - radiation effects
/ Dose fractionation
/ Dose response relationship
/ Dose-Response Relationship, Radiation
/ Fractionation
/ Geometric planes
/ Linear regression
/ Mathematical models
/ Mathematics
/ Models, Biological
/ Parametric models
/ Radiation dosage
/ Radiation dose response relationship
/ Radiotherapy
/ Radiotherapy Dosage
1976
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Do you wish to request the book?
Comparison of Mathematical Models for Radiation Fractionation
by
McLarty, Jerry W.
, Hethcote, Herbert W.
, Thames, Howard D.
in
Cell Survival - radiation effects
/ Dose fractionation
/ Dose response relationship
/ Dose-Response Relationship, Radiation
/ Fractionation
/ Geometric planes
/ Linear regression
/ Mathematical models
/ Mathematics
/ Models, Biological
/ Parametric models
/ Radiation dosage
/ Radiation dose response relationship
/ Radiotherapy
/ Radiotherapy Dosage
1976
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Comparison of Mathematical Models for Radiation Fractionation
Journal Article
Comparison of Mathematical Models for Radiation Fractionation
1976
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Overview
Radiation fractionation data can be plotted in four planes: log N-log D, dose-reciprocal total dose, dose-response, and dose-recovery dose. Properties of curves in these planes corresponding to five models are developed. One model assumes that total dose is a power function of the number of fractions; the other four models assume that the dose-log surviving fraction curve is described by (1) a multitarget, (2) a two component (product of single-hit and multitarget factors), (3) a quadratic, and (4) a cubic function, respectively. Several nonlinear regression criteria are defined and corresponding computer programs have been developed. Best fits for the five models are found for three specific data sets involving normal tissues in mice. One regression criterion and three models are shown to be unsuitable.
Publisher
Academic Press, Inc
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