Centro Diagnostico Italiano, Milano, Italy.
Immun Ageing. 2010 Dec 16;7 Suppl 1(Suppl 1):S3. doi: 10.1186/1742-4933-7-S1-S3.
An individual patient is not the average representative of the population. Rather he or she is a person with unique characteristics. An intervention may be effective for a population but not necessarily for the individual patient. The recommendation of a guideline may not be right for a particular patient because it is not what he or she wants, and implementing the recommendation will not necessarily mean a favourable outcome.The author will describe a reconfiguration of medical thought which originates from non linear dynamics and chaos theory. The coupling of computer science and these new theoretical bases coming from complex systems mathematics allows the creation of "intelligent" agents able to adapt themselves dynamically to problem of high complexity: the Artificial Adaptive Systems, which include Artificial Neural Networks( ANNs ) and Evolutionary Algorithms ( EA).ANNs and EA are able to reproduce the dynamical interaction of multiple factors simultaneously, allowing the study of complexity; they can also help medical doctors in making decisions under extreme uncertainty and to draw conclusions on individual basis and not as average trends. These tools can allow a more efficient Technology Transfer from the Science of Medicine to the Real World overcoming many obstacles responsible for the present translational failure. They also contribute to a new holistic vision of the human subject contrasting the statistical reductionism which tends to squeeze or even delete the single subject sacrificing him to his group of belongingness. A remarkable contribution to this individual approach comes from Fuzzy Logic, according to which there are no sharp limits between opposite things, like health and disease. This approach allows to partially escape from probability theory trap in situations where is fundamental to express a judgment based on a single case and favours a novel humanism directed to the management of the patient as individual subject.
个体患者并非人群的平均代表。相反,他或她是具有独特特征的个体。一种干预措施可能对人群有效,但不一定对个体患者有效。指南的推荐可能并不适合特定患者,因为这不是他或她想要的,并且实施该推荐并不一定意味着有利的结果。
作者将描述一种源于非线性动力学和混沌理论的医学思维重构。计算机科学与来自复杂系统数学的这些新理论基础的结合,允许创建“智能”代理,能够动态地适应高度复杂的问题:人工自适应系统,包括人工神经网络(ANNs)和进化算法(EA)。
ANNs 和 EA 能够同时再现多个因素的动态相互作用,从而允许研究复杂性;它们还可以帮助医生在极端不确定的情况下做出决策,并根据个体基础而不是平均趋势得出结论。这些工具可以使医学科学向现实世界的技术转移更加高效,克服了导致目前转化失败的许多障碍。它们还促成了对人类主体的新整体视角,与倾向于挤压甚至删除单个主体以牺牲他的所属群体的统计还原论形成对比。模糊逻辑为此种个体方法做出了显著贡献,根据模糊逻辑,相反的事物之间没有明显的界限,例如健康和疾病。这种方法允许在基于单个案例表达判断的情况下部分摆脱概率论的陷阱,并有利于一种新颖的人文主义,旨在将患者作为个体主体进行管理。