基于非线性方法的癌症临床医学数据分析及干细胞理论研究

发布时间：2018-06-08 00:36

本文选题：非线性 + 癌症　；参考：《浙江大学》2012年硕士论文

【摘要】：癌症是严重危害人类生命和健康的重大疾病,一直是现代医学和生物学研究的重点和热点。而目前现有的分析方法对癌症产生机制缺乏有力的解释。同时,随着医疗器械的不断创新以及计算机辅助诊断技术的进步,海量的临床数据处理也是摆在医学工作者面前的难题之一近年来,非线性逐渐成为医学工作者关注的热点。非线性理论是以非线性现象为研究对象的基础科学。人体系统本身就是一个复杂的非线性系统,这使得非线性方法在研究人体或医学对象时有着良好的适应性。同时,非线性方法在处理大数据量问题时也有着其独特的优势。因此将非线性理论和非线性方法引入医学研究领域特别是癌症研究领域,对医学问题的研究和解决有着重要的意义。本文以非线性系统方法为工具,对非线性理论在医学领域应用、临床医学数据(脑电信号、胃癌血清蛋白质谱数据)分析建模、癌症干细胞理论等进行了深入的探讨和研究。主要包括如下几个方面的工作： 1、脑电非线性分析提取了麻醉患者脑电信号的时域参数(近似熵、信息熵、复杂度)、频域参数(总功率、功率谱重心)以及非线性参数(关联维、最大李雅普诺夫指数),分析了整个麻醉过程中大脑活跃程度的变化和特点。通过各种参数与BIS (Bispectal Index,双频谱指数)标准值的对比,得到了各种参数对麻醉深度相关性程度,具有一定的商业应用价值。 2、胃癌血清蛋白质谱数据的分析与处理对胃癌血清蛋白质谱数据进行了分析与建模,针对Seldi-tof-MS(表面增强激光解吸电离飞行-时间质谱)技术的不足,设计了特定的实验方案设计,校正了其偏差。实验结果证明,分类结果得到了有效地提高。开发了相应的软件处理分析平台,并申请了软件著作权。 3、混沌映射对癌症转移现象的解释探索提出了癌细胞来源于干细胞分化的观点。以混沌映射(Henon方程)为工具,探索建立了相应的系统模型,并对癌症的产生、发展和转移等现象作了相应的解释和分析。
[Abstract]:Cancer is a major disease that seriously endangers human life and health, and has always been the focus and hotspot of modern medicine and biology. However, the existing analytical methods do not have a strong explanation for the mechanism of cancer production. At the same time, with the continuous innovation of medical devices and the progress of computer-aided diagnosis technology, massive clinical data processing is one of the difficult problems facing medical workers. In recent years, nonlinearity has gradually become the focus of medical workers' attention. Nonlinear theory is the basic science of nonlinear phenomena. Human body system is a complex nonlinear system, which makes nonlinear method have good adaptability in the study of human body or medical object. At the same time, the nonlinear method has its unique advantages in dealing with the problem of large amount of data. Therefore, the introduction of nonlinear theory and nonlinear methods into the field of medical research, especially in the field of cancer, is of great significance to the research and solution of medical problems. The application of nonlinear theory in the field of medicine, the analysis and modeling of clinical medical data (EEG, serum protein spectrum data of gastric cancer) and the theory of cancer stem cell were deeply discussed and studied. The main work includes the following aspects: 1. The time domain parameters (approximate entropy, information entropy, complexity), frequency domain parameters (total power) of EEG signals in anesthetized patients were extracted by EEG nonlinear analysis. Power spectral center of gravity) and nonlinear parameters (correlation dimension, maximum Lyapunov exponent) were used to analyze the changes and characteristics of brain activity during anesthesia. By comparing various parameters with the standard value of BIS Bispectal Index (bispectal index), the correlation of various parameters to the depth of anesthesia was obtained. 2The analysis and processing of serum protein spectrum data of gastric cancer were carried out to analyze and model the serum protein spectrum data of gastric cancer, aiming at the deficiency of Seldi-tof-MS (surface enhanced laser desorption ionization time-of-flight mass spectrometry) technology. A specific experimental scheme is designed and its deviation is corrected. The experimental results show that the classification results are improved effectively. The corresponding software processing and analysis platform is developed, and the software copyright is applied. 3. Chaos mapping is used to explain the phenomenon of cancer metastasis. The viewpoint that cancer cells are derived from stem cell differentiation is put forward. Using the chaotic mapping Henon equation as a tool, this paper explores and establishes a corresponding system model, and gives a corresponding explanation and analysis of the occurrence, development and metastasis of cancer.
【学位授予单位】：浙江大学
【学位级别】：硕士
【学位授予年份】：2012
【分类号】：R319

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