Higgins John P
Cardiology Section, Noninvasive Cardiac Laboratories, VA Boston Healthcare System, Harvard Medical School, Boston, Massachusetts 02132, USA.
Yale J Biol Med. 2002 Sep-Dec;75(5-6):247-60.
Many achievements in medicine have come from applying linear theory to problems. Most current methods of data analysis use linear models, which are based on proportionality between two variables and/or relationships described by linear differential equations. However, nonlinear behavior commonly occurs within human systems due to their complex dynamic nature; this cannot be described adequately by linear models. Nonlinear thinking has grown among physiologists and physicians over the past century, and non-linear system theories are beginning to be applied to assist in interpreting, explaining, and predicting biological phenomena. Chaos theory describes elements manifesting behavior that is extremely sensitive to initial conditions, does not repeat itself and yet is deterministic. Complexity theory goes one step beyond chaos and is attempting to explain complex behavior that emerges within dynamic nonlinear systems. Nonlinear modeling still has not been able to explain all of the complexity present in human systems, and further models still need to be refined and developed. However, nonlinear modeling is helping to explain some system behaviors that linear systems cannot and thus will augment our understanding of the nature of complex dynamic systems within the human body in health and in disease states.
医学领域的许多成就都源于将线性理论应用于各种问题。当前大多数数据分析方法都使用线性模型，这些模型基于两个变量之间的比例关系和/或由线性微分方程描述的关系。然而，由于人体系统具有复杂的动态特性，非线性行为在其中普遍存在；线性模型无法充分描述这种行为。在过去的一个世纪里，生理学家和医生中非线性思维不断发展，非线性系统理论开始被应用于协助解释、阐释和预测生物现象。混沌理论描述了一些元素表现出对初始条件极其敏感、不会重复但却是确定性的行为。复杂性理论比混沌理论更进一步，试图解释动态非线性系统中出现的复杂行为。非线性建模仍无法解释人体系统中存在的所有复杂性，还需要进一步完善和发展更多模型。然而，非线性建模有助于解释一些线性系统无法解释的系统行为，从而增进我们对人体在健康和疾病状态下复杂动态系统本质的理解。
