Statistical Modeling in Biomedical Research : Contemporary Topics and Voices in the Field. 1st ed. 2020

種類:

電子ブック

責任表示:

edited by Yichuan Zhao, Ding-Geng (Din) Chen

出版情報:

Cham : Springer International Publishing : Imprint: Springer, 2020

著者名:

• Zhao, Yichuan.
• Chen, Ding-Geng (Din).
• SpringerLink (Online service)

シリーズ名:

Emerging Topics in Statistics and Biostatistics ;

ISBN:

9783030334161 [3030334163]    

注記:

Preface -- Part I: Next Generation Sequence Data Analysis -- 1. Modeling Species Specific Gene Expression Across Multiple Regions in the Brain -- 2. Classification of EEG Motion Artifact Signals Using Spatial ICA -- 3. Weighted K-means Clustering with Observation Weight for Single-cell Epigenomic Data -- 4. Discrete Multiple Testing in Detecting Differential Methylation Using Sequencing Data -- Part II: Deep Learning, Precision Medicine and Applications -- 5. Prediction of Functional Markers of Mass Cytometry Data via Deep Learning -- 6. Building Health Application Recommender System Using Partially Penalized Regression -- 7. Hierarchical Continuous Time Hidden Markov Model, with Application in Zero-Inflated Accelerometer Data -- Part III: Large Scale Data Analysis and its Applications -- 8. Privacy Preserving Feature Selection Via Voted Wrapper Method For Horizontally Distributed Medical Data -- 9. Improving Maize Trait through Modifying Combination of Genes -- 10. Molecular Basis of Food Classification in T
This edited collection discusses the emerging topics in statistical modeling for biomedical research. Leading experts in the frontiers of biostatistics and biomedical research discuss the statistical procedures, useful methods, and their novel applications in biostatistics research. Interdisciplinary in scope, the volume as a whole reflects the latest advances in statistical modeling in biomedical research, identifies impactful new directions, and seeks to drive the field forward. It also fosters the interaction of scholars in the arena, offering great opportunities to stimulate further collaborations. This book will appeal to industry data scientists and statisticians, researchers, and graduate students in biostatistics and biomedical science. It covers topics in: Next generation sequence data analysis Deep learning, precision medicine, and their applications Large scale data analysis and its applications Biomedical research and modeling Survival analysis with complex data structure and its applications.

ローカル注記:

学内専用E-BOOKS (local access only)