Medicine
and health care are currently faced with a significant rise in their
complexity. This is partly due to the progress made during the past three
decades in the fundamental biological understanding of the causes of health and
disease at the molecular, (sub)cellular, and organ level. Since the end of the
1970s, when knowledge representation and reasoning in the biomedical field
became a separate area of research, huge progress has been made in the
development of methods and tools that are finally able to impact on the way
medicine is being practiced.

 

Even
though there are huge differences in the techniques and methods used by
biomedical researchers, there is now an increasing tendency to share research
results in terms of formal knowledge representation methods, such as
ontologies, statistical models, network models, and mathematical models. As
there is an urgent need for health-care professionals to make better decisions,
computer-based support using this knowledge is now becoming increasingly important.
It may also be the only way to integrate research results from the different
parts of the spectrum of biomedical and clinical research.

 











The
aim of this book is to shed light on developments in knowledge representation
at different levels of biomedical application, ranging from human biology to
clinical guidelines, and using different techniques, from probability theory
and differential equations to logic. The book starts with two introductory
chapters followed by 18 contributions organized in the following topical
sections: diagnosis of disease; monitoring of health and disease and
conformance; assessment of health and personalization; prediction and prognosis
of health and disease; treatment of disease; and recommendations.