- Tuesday. Apr 21st, 2015
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Recent Advances in Quantitative Methods in Cancer and Human Health Risk Assessment
This volume has been designed by Lutz Edler (Biostatistics Unit of the German Cancer Research Center in Heidelberg) and Christos P. Kitsos (Department of Mathematics of the Technical Educational Institute in Athens) to present concepts and methods for cancer and human health risk assessment. A comprehensive text accounts for the wealth of new biological data as well as new biological, toxicological and medical approaches to be used for risk assessment. Mathematical, statistical and computational methods are presented for exposure assessment, hazard identification, dose-response modelling and hazard characterization. This volume has been compiled with the intention of bridging different approaches to the risk assessment problem through 25 contributions written by a group of distinct expert authorities. The breadth of this approach is reflected in the number and the content of about 1000 references, a bibliographic source which may also bridge an existing gap in risk assessment literature.
Various topics such as biological carcinogenesis theories, stochastic carcinogenesis models, modelling for cancer survival and cancer screening studies, doseresponse modelling, statistical evaluation methods, the Bayesian approach to uncertainty, design of experiments, the benchmark dose approach, biochemical and molecular biomarkers, genomic data and case studies for health risk assessment are addressed by well-known scientists who present recent work and points of view on the best risk assessment methodologies.
We believe that this book will contribute to a better transfer of risk assessment methodology to academic researchers as well as to risk assessors and regulators. This text should support all those interested in this challenging and exciting applied science: researchers in medical science, biology, toxicology, statistics or mathematics, risk assessors or stakeholders involved in the day-to-day process of risk assessment, and teachers of biomathematics and biostatistics planning a graduate– level course with real-life applications.