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In this Information Age, the practices of clinical medicine should
no longer be based on what clinical doctors actively know. Rather,
all of the importantly practice-relevant knowledge should not only
already exist but also be codified in cyberspace, in directly
practice-guiding 'expert systems' -- for the benefit of both
doctors and patients everywhere. Each of these systems
(discipline-specific) would, prompted by a particular type of case
presentation, present the doctor a questionnaire specific to cases
of the type at issue, and document the doctor's answers to the
questions. If at issue would be a case of complaint about a
(particular type of) sickness, the system would translate the
resulting diagnostic profile of the case into the corresponding
probabilities of the illnesses to be considered. Similarly, if at
issue would be an already-diagnosed case of a particular illness,
the system would ask about, and record, the relevant elements in
the prognostic profile of the case and then translate this profile
into the probabilities of various outcomes to be considered,
probabilities specific to the choice of treatment and prospective
time in addition to that profile. And besides, these systems would
analogously address the causal origin -- etiogenesis -- of cases of
particular types of illness. While the requisite knowledge-base for
these systems -- notably for the probabilities in them -- has not
been addressed by such 'patient-oriented' clinical research as has
been conducted (very extensively) up to now, this book delineates
the nature of the suitably-transformed research (gnostic). The
critically-transformative innovation in the research is the
studies' focus on Gnostic Probability Functions -- dia-, etio-, and
prognostic -- in the framework of logistic regression models. This
book also presents a vision of how this critically-transformative
research would most expeditiously be provided for and also
conducted, among select sets of academic teaching hospitals.
This concise but wide-ranging handbook reviews the epidemiology of neurological disease and the treatment and prognosis of all major diseases of the nervous system. Part One offers essential guidance for clinicians to quantitative methods in research, including genetic epidemiology, decision analysis, meta-analysis, outcomes research, and survival analysis. Thus it provides a good understanding of the evidence underlying clinical management. The second part is devoted to individual neurological diseases, covering etiology, diagnosis, prognosis, interventions, and implications for clinical practice. With contributions from leading international authorities, this book is an invaluable guide to clinical decision-making for neurologists and others involved in the management of neurological disease.
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