Statistical Research Methods for Dermatologists and Plastic Surgeons | 52.33 MB
Title: Statistical Research Methods for Dermatologists and Plastic Surgeons
Author: Yichuan Zhao, (Din) Ding-Geng Chen
Category: Nonfiction, Health & Well Being, Medical, Reference, Biostatistics, Research
Language: English | 364 Pages | ISBN: 9783030724375
Description:
This book brings together the voices of leading experts in the frontiers of biostatistics, biomedicine, and the health sciences to discuss the statistical procedures, useful methods, and novel applications in biostatistics research. It also includes discussions of potential future directions of biomedicine and new statistical developments for health research, with the intent of stimulating research and fostering the interactions of scholars across health research related disciplines. Topics covered include:
Health data analysis and applications to EHR data
Clinical trials, FDR, and applications in health science
Big network analytics and its applications in GWAS
Survival analysis and functional data analysis
Graphical modelling in genomic studies
The book will be valuable to data scientists and statisticians who are working in biomedicine and health, other practitioners in the health sciences, and graduate students and researchers in biostatistics and health.
This book brings together the voices of leading experts in the frontiers of biostatistics, biomedicine, and the health sciences to discuss the statistical procedures, useful methods, and novel applications in biostatistics research. It also includes discussions of potential future directions of biomedicine and new statistical developments for health research, with the intent of stimulating research and fostering the interactions of scholars across health research related disciplines. Topics covered include:
Health data analysis and applications to EHR data
Clinical trials, FDR, and applications in health science
Big network analytics and its applications in GWAS
Survival analysis and functional data analysis
Graphical modelling in genomic studies
The book will be valuable to data scientists and statisticians who are working in biomedicine and health, other practitioners in the health sciences, and graduate students and researchers in biostatistics and health.
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