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Cancer: Modeling the distribution of...
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Russo, Donna A.
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Cancer: Modeling the distribution of sizes of detectable metastases.
紀錄類型:
書目-語言資料,印刷品 : Monograph/item
正題名/作者:
Cancer: Modeling the distribution of sizes of detectable metastases./
作者:
Russo, Donna A.
面頁冊數:
87 p.
附註:
Source: Masters Abstracts International, Volume: 49-01, page: 0478.
Contained By:
Masters Abstracts International49-01.
標題:
Applied Mathematics. -
電子資源:
http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=1486390
ISBN:
9781124247809
Cancer: Modeling the distribution of sizes of detectable metastases.
Russo, Donna A.
Cancer: Modeling the distribution of sizes of detectable metastases.
- 87 p.
Source: Masters Abstracts International, Volume: 49-01, page: 0478.
Thesis (M.S.)--California State University, Long Beach, 2010.
As life expectancy grows longer in developed nations, the possibility of falling prey to some form of cancer becomes more and more likely. More significantly, while many cancers have become curable or may be sent into remission by palliative treatments, other forms of cancer become metastatic and there is often little that can be done to overcome the disease. Therefore, in an effort to better understand the process of metastatic cancer, researchers in the fields of medicine, biology, epidemiology, clinical investigation, biomathematics, and biostatistics work together to find ways to extend the lives of these cancer patients. Understanding of this process can be facilitated through the use of mathematical, statistical, and stochastic models that approximate progress in the varying stages of this often devastating disease. This thesis will synthesize two existing models for the distribution of sizes of detectable metastases.
ISBN: 9781124247809Subjects--Topical Terms:
1669109
Applied Mathematics.
Cancer: Modeling the distribution of sizes of detectable metastases.
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As life expectancy grows longer in developed nations, the possibility of falling prey to some form of cancer becomes more and more likely. More significantly, while many cancers have become curable or may be sent into remission by palliative treatments, other forms of cancer become metastatic and there is often little that can be done to overcome the disease. Therefore, in an effort to better understand the process of metastatic cancer, researchers in the fields of medicine, biology, epidemiology, clinical investigation, biomathematics, and biostatistics work together to find ways to extend the lives of these cancer patients. Understanding of this process can be facilitated through the use of mathematical, statistical, and stochastic models that approximate progress in the varying stages of this often devastating disease. This thesis will synthesize two existing models for the distribution of sizes of detectable metastases.
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