Cancer Clinical Data Analysis And Stem Cell Research Based On Nonlinear Theory

Cancer, known as "malignant tumor", is a significant medical and social problem, at present due to the lack of a powerful explanation for the mechanism of cancer, and with the innovation of medical devices and the advances in computer technology, clinical data have increased dramatically, so it has formed a threat to medical researchers for processing them。In recent years, nonlinear system gradually becomes a new hot spot of the medical researchers。 It is nature to apply the nonlinear methods to the study the human body or medical objects since human body is nonlinear as a system。 Moreover, the nonlinear methods also have its unique advantages in dealing with huge amounts data。 Therefore, nonlinear theory and nonlinear methods in the field of medical research, especially cancer research, shows an important significance, which has commercial value。This thesis introduces nonlinear methods as a tool to do the clinical data analysis and modeling, cancer stem cell theory discussion。 The main works of this thesis are as follows:1、EEG (electroencephalogram) is used to assess the consciousness lever of the brains。In this thesis, we extract the time parameters, frequency parameters and nonlinear parameters from EEG signal to get the depth of anesthesia estimation。The result shows that there is a good relevance between the parameters trends and the brain activity during the anesthesia process。2、The reproducibility of mass spectrometry (MS) data collected using SELDI-TOF has been questioned correspondingly its application has been limited, this thesis tests the reproducibility of SELDI data over time and proposes a method to adjust the offset of MS data collected in different time。We also provide a software using Matlab and C language to do the data analysis。3、This thesis proposes a viewpoint that cancer cells derived from stem cells differentiation。We uses chaotic map (the Henon equation) as a tool to establish the dynamic model of the human system, then analyzes some cancer phenomena。...