Finitzo T, Pool K D, Chapman S B
Neuroscience Research Center, Dallas, Texas 75220.
Ann N Y Acad Sci. 1991;620:57-72. doi: 10.1111/j.1749-6632.1991.tb51574.x.
No single technology in isolation can provide a full view of the anatomoclinical principles evident in the clinical populations we study. The dynamic nature of quantitative electrophysiology makes it an ideal complement to anatomic and metabolic imaging. The statistical conundrum it has presented may be resolved by the approach incorporated in CART. The intent of this study was to examine QEEG and CART in the evaluation of the neurologic bases of a well-defined behavioral disorder like aphasia. The combined power of QEEG and CART yielded objective electrophysiologic methods to predict aphasia that rival the reliability of the language examination. Such success is unprecedented. This success allows us to incorporate QEEG and CART into our technological armamentarium and to return to the evaluation of less well-understood disorders with confidence in both our findings and anatomoclinical principles we derive from them.
没有任何一项单独的技术能够全面展现我们所研究的临床人群中明显存在的解剖临床学原理。定量电生理学的动态特性使其成为解剖学和代谢成像的理想补充。它所呈现的统计学难题或许可以通过分类与回归树（CART）所采用的方法来解决。本研究的目的是在评估失语症这类明确的行为障碍的神经学基础时，检验定量脑电图（QEEG）和分类与回归树（CART）。定量脑电图（QEEG）和分类与回归树（CART）相结合的力量产生了客观的电生理方法来预测失语症，其可靠性可与语言检查相媲美。这样的成功是前所未有的。这一成功使我们能够将定量脑电图（QEEG）和分类与回归树（CART）纳入我们的技术手段，并满怀信心地重新评估那些了解较少的疾病，因为我们对研究结果以及从中得出的解剖临床学原理都充满信心。
