Biomedical research methodology based on GH-Method: math-physical medicine (No. 310)

Gerald C. Hsu
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引用次数: 33

Abstract

This paper discusses the author’s biomedical research work based on the GH-Method: math-physical medicine (MPM) approach over the past decade. This is significantly different from the traditional medical research using biochemical approach and simple statistical methods. He uses his own type 2 diabetes (T2D) metabolic conditions as a case study including several application examples as illustrations and explanations of the MPM methodology. The MPM methodology will be described, then followed by 10 application examples to show how he applied his knowledge and disciplines in mathematics, physics, engineering modeling, computer science tools, and psychology during his 10-years of biomedical research, especially in the domain of lifestyle, metabolism, chronic diseases, diabetes, cardiovascular diseases, and renal complications. The following list highlights the math-physical concepts, theories, principles, or equations used in the 10 application examples: 1. Topology, finite element method 2. Time-domain analysis, correlation and regression model, pattern recognition, segmentation analysis 3. Signal processing, trial and error method, regression analysis 4. Artificial intelligence (AI) auto-correction, quantum mechanics, safety margin of engineering design 5. Optical physics, AI, perturbation theory of quantum mechanics 6. Wave theory, Fourier transform, frequency-domain analysis 7. Structural engineering modeling, solid mechanics (both elastic and plastic), fluids dynamics, energy theory 8. Pattern recognition, behavior psychology 9. Spatial analysis, time-series analysis 10. Big data analytics, AI, software engineering Using MPM, a non-traditional medical research methodology, provides many quantitative proofs with a high degree of accuracy (higher precision) compared to other disease research results. Medicine is based on biology and chemistry, while biology, chemistry, and engineering are based on physics, and physics is based on mathematics. Logically, mathematics is the mother of all sciences. When we explore our application problems down to the foundation level, we can discover more facts and deeper truths. This is the logical essence of “math-physical medicine.” Using this MPM model, the accuracy of medical evaluations, along with the precision of predictive models can be greatly improved, with dramatic benefits to the patients.
基于GH-Method的生物医学研究方法学:数理医学(第310期)
本文论述了作者近十年来基于GH-Method:数学-物理医学(MPM)方法的生物医学研究工作。这与传统的医学研究采用生化方法和简单的统计方法有明显的不同。他以自己的2型糖尿病(T2D)代谢状况作为案例研究,包括几个应用实例作为MPM方法的说明和解释。本文将介绍MPM方法,然后通过10个应用实例来展示他如何在他10年的生物医学研究中应用他在数学、物理、工程建模、计算机科学工具和心理学方面的知识和学科,特别是在生活方式、代谢、慢性疾病、糖尿病、心血管疾病和肾脏并发症领域。下面的列表突出了10个应用示例中使用的数学物理概念、理论、原理或方程:拓扑学、有限元法2。时域分析,相关与回归模型,模式识别,分割分析3。信号处理,试错法,回归分析4。人工智能(AI)自动校正、量子力学、工程设计安全裕度光学物理、人工智能、量子力学微扰理论波动理论,傅里叶变换,频域分析结构工程建模,固体力学(包括弹性和塑性),流体动力学,能量理论模式识别,行为心理学空间分析、时间序列分析使用MPM这一非传统的医学研究方法,与其他疾病研究成果相比,提供了许多准确度高(精度更高)的定量证据。医学以生物学和化学为基础,而生物学、化学和工程学以物理学为基础,物理学以数学为基础。从逻辑上讲,数学是一切科学之母。当我们深入到应用问题的基础层面时,我们可以发现更多的事实和更深刻的真理。这就是“数理医学”的逻辑本质。使用该模型,可以大大提高医学评估的准确性,以及预测模型的精度,为患者带来巨大的好处。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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