Biomedical Science


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Introduction to Mathematical Oncology

Yang Kuang, John D. Nagy, Steffen E. Eikenberry
February 18, 2016

Introduction to Mathematical Oncology presents biologically well-motivated and mathematically tractable models that facilitate both a deep understanding of cancer biology and better cancer treatment designs. It covers the medical and biological background of the diseases, modeling issues, and...

Synergic Influence of Gaseous, Particulate, and Biological Pollutants on Human Health

Jozef S. Pastuszka
November 23, 2015

Synergic Influence of Gaseous, Particulate, and Biological Pollutants on Human Health is a unique merger of two divergent parts. The first part is a presentation of the existing knowledge on the characteristics of basic air pollutants and their documented impact on human health. The focus is on the...

Nutrition in Public Health: Principles, Policies, and Practice, Second Edition

Arlene Spark, Lauren M. Dinour, Janel Obenchain
October 05, 2015

This second edition of a bestseller, Nutrition in Public Health: Principles, Policies, and Practice focuses on the role of the federal government in determining nutrition policy and influencing practice. Beginning with an overview of public health principles, the book examines the application of...

Dynamical Biostatistical Models

Daniel Commenges, Helene Jacqmin-Gadda
October 02, 2015

Dynamical Biostatistical Models presents statistical models and methods for the analysis of longitudinal data. The book focuses on models for analyzing repeated measures of quantitative and qualitative variables and events history, including survival and multistate models. Most of the advanced...

Genetics of Complex Disease

Peter Donaldson, Ann Daly, Luca Ermini, Debra Bevitt
August 25, 2015

Genetics of Complex Disease examines how the identification of genetic variations that increase or reduce the risk of common, genetically complex, diseases can be used to improve our understanding of the pathology of many common diseases; enable better patient management and care; and help with...

Data Analysis with Competing Risks and Intermediate States

Ronald B. Geskus
July 14, 2015

Data Analysis with Competing Risks and Intermediate States explains when and how to use models and techniques for the analysis of competing risks and intermediate states. It covers the most recent insights on estimation techniques and discusses in detail how to interpret the obtained results....

Spatio-Temporal Methods in Environmental Epidemiology

Gavin Shaddick, James V. Zidek
June 24, 2015

Teaches Students How to Perform Spatio-Temporal Analyses within Epidemiological Studies Spatio-Temporal Methods in Environmental Epidemiology is the first book of its kind to specifically address the interface between environmental epidemiology and spatio-temporal modeling. In response to the...

Modelling Interactions Between Vector-Borne Diseases and Environment Using GIS

Hassan M. Khormi, Lalit Kumar
May 01, 2015

Master GIS Applications on Modelling and Mapping the Risks of Diseases Infections transmitted by mosquitoes, ticks, triatomine bugs, sandflies, and black flies cause significant rates of death and disease, especially in developing countries. Why are certain places more susceptible to vector-borne...

Modeling to Inform Infectious Disease Control

Niels G. Becker
April 28, 2015

Effectively Assess Intervention Options for Controlling Infectious Diseases Our experiences with the human immunodeficiency virus (HIV), severe acute respiratory syndrome (SARS), and Ebola virus disease (EVD) remind us of the continuing need to be vigilant against the emergence of new infectious...

Health Technology Assessment: Using Biostatistics to Break the Barriers of Adopting New Medicines

Robert B. Hopkins, MA, MBA, PhD, Ron Goeree, MA
April 10, 2015

The term health technology refers to drugs, devices, and programs that can improve and extend quality of life. As decision-makers struggle to find ways to reduce costs while improving health care delivery, health technology assessments (HTA) provide the evidence required to make better-informed...

Bayesian Inference for Partially Identified Models: Exploring the Limits of Limited Data

Paul Gustafson
April 01, 2015

Bayesian Inference for Partially Identified Models: Exploring the Limits of Limited Data shows how the Bayesian approach to inference is applicable to partially identified models (PIMs) and examines the performance of Bayesian procedures in partially identified contexts. Drawing on his many years...

Mendelian Randomization: Methods for Using Genetic Variants in Causal Estimation

Stephen Burgess, Simon G. Thompson
March 06, 2015

Presents the Terminology and Methods of Mendelian Randomization for Epidemiological Studies Mendelian randomization uses genetic instrumental variables to make inferences about causal effects based on observational data. It, therefore, can be a reliable way of assessing the causal nature of risk...