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Signal Detection for Medical Scientists: Likelihood Ratio Based
Test-Based Methodology presents the data mining techniques with
focus on likelihood ratio test (LRT) based methods for signal
detection. It emphasizes computational aspect of LRT methodology
and is pertinent for first-time researchers and graduate students
venturing into this interesting field. The book is written as a
reference book for professionals in pharmaceutical industry,
manufactures of medical devices, and regulatory agencies. The book
deals with the signal detection in drug/device evaluation, which is
important in the post-market evaluation of medical products, and in
the pre-market signal detection during clinical trials for
monitoring procedures. It should also appeal to academic
researchers, and faculty members in mathematics, statistics,
biostatistics, data science, pharmacology, engineering,
epidemiology, and public health. Therefore, this book is well
suited for both research and teaching. Key Features: Includes a
balanced discussion of art of data structure, issues in signal
detection, statistical methods and analytics, and implementation of
the methods. Provides a comprehensive summary of the LRT methods
for signal detection including the basic theory and extensions for
varying datasets that may be large post-market data or pre-market
clinical trial data. Contains details of scientific background,
statistical methods, and associated algorithms that a reader can
quickly master the materials and apply methods in the book on one's
own problems
This book presents recent results on nonlinear parabolic-hyperbolic
coupled systems such as the compressible Navier-Stokes equations,
and liquid crystal system. It summarizes recently published
research by the authors and their collaborators, but also includes
new and unpublished material. All models under consideration are
built on compressible equations and liquid crystal systems. This
type of partial differential equations arises not only in many
fields of mathematics, but also in other branches of science such
as physics, fluid dynamics and material science.
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