Full Description
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.
Contents
How
to Read the Book "Foundations of Biomedical Knowledge Representation".- An
Introduction to Knowledge Representation and Reasoning in Healthcare.- Representing Knowledge for
Clinical Diagnostic Reasoning.- Automated Diagnosis of Breast Cancer on
Medical.- Monitoring in the Healthcare Setting.- Conformance Verification of
Clinical Guidelines in Presence of Computerized and Human-Enhanced.- Modelling and Monitoring
the Individual Patient in Real Time.- Personalised Medicine: Taking a New Look
at the Patient.- Graphical Modelling in Genetics and Systems Biology.- Chain
Graphs and Gene Networks.- Prediction and Prognosis of Health and Disease.- Trajectories
Through the Disease Process: Cross Sectional and
Longitudinal Studies.- Dynamic Bayesian Network for
Cervical Cancer Screening.- Modeling Dynamic Processes with Memory by Higher
Order Temporal
Models.- Treatment of Disease: The Role of Knowledge Representation for
Treatment Selection.- Predicting Adverse Drug Events from Electronic Medical
Records.- User Modelling for Patient Tailored Virtual Rehabilitation.- Supporting
Physicians and Patients through Recommendation: Guidelines and Beyond.- A
Hybrid Approach to the Verification of Computer Interpretable Guidelines.- Aggregation of Clinical
Evidence Using Argumentation.
