癫痫的统计方法

English | 2024 | ISBN: 1032184353 | 419 pages | True PDF EPUB | 42.59 MB

Epilepsy research promises new treatments and insights into brain function, but statistics and machine learning are paramount for extracting meaning from data and enabling discovery. Statistical Methods in Epilepsy provides a comprehensive introduction to statistical methods used in epilepsy research. Written in a clear, accessible style by leading authorities, this textbook demystifies introductory and advanced statistical methods, providing a practical roadmap that will be invaluable for learners and experts alike. Topics include a primer on version control and coding, pre-processing of imaging and electrophysiological data, hypothesis testing, generalized linear models, survival analysis, network analysis, time-series analysis, spectral analysis, spatial statistics, unsupervised and supervised learning, natural language processing, prospective trial design, pharmacokinetic and pharmacodynamic modeling, and randomized clinical trials. Features: Provides a comprehensive introduction to statistical methods employed in epilepsy research Divided into four parts: Basic Processing Methods for Data Analysis; Statistical Models for Epilepsy Data Types; Machine Learning Methods; and Clinical Studies Covers methodological and practical aspects, as well as worked-out examples with R and Python code provided in the online supplement Includes contributions by experts in the field This handbook targets clinicians, graduate students, medical students, and researchers who seek to conduct quantitative epilepsy research. The topics covered extend broadly to quantitative research in other neurological specialties and provide a valuable reference for the field of neurology.

癫痫研究为治疗和理解大脑功能提供了新的治疗方法和洞见，但统计数据和机器学习在从数据中提取意义并促进发现方面至关重要。《癫痫统计方法》提供了一个全面的介绍，介绍了用于癫痫研究中的统计方法。由领域内的权威专家撰写的这本书以清晰、易于理解的方式编写，消除了初学者和高级统计学方法之间的神秘感，为学习者和专业人士提供了宝贵的实用路线图。内容涵盖数据分析的基本处理方法、癫痫类型的数据模型、机器学习方法以及临床试验设计等方面。包括未监督学习和监督学习、自然语言处理、前瞻性试验设计、药代动力学和药效动力学建模、随机对照临床试验等内容。特色：全面介绍在癫痫研究中使用的统计方法，分为四部分：数据分析的基本处理方法；用于癫痫数据类型的统计模型；机器学习方法；以及临床研究这部分涵盖方法论和实用方面，包括在线补充提供的R和Python代码实例。包含领域专家的贡献这本书的目标受众是希望进行定量癫痫研究的临床医生、研究生学生、医学院学生以及研究人员。涵盖的主题广泛适用于神经病学领域的其他定量研究，并为该领域提供了宝贵的参考资料。

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