By Eta S. Berner
Development at the good fortune of the former versions, this absolutely up-to-date booklet once more brings jointly all over the world specialists to demonstrate the underlying technological know-how and day by day use of choice help structures in scientific and academic settings.
Topics mentioned include:
-Mathematical Foundations of determination help Systems
-Design and Implementation Issues
-Ethical and felony matters in determination Support
-Clinical Trials of data Interventions
-Hospital-Based determination Support
-Real global Case Studies
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Additional info for Clinical decision support systems : theory and practice
Signs, symptoms, laboratory and radiographic tests). Maintaining the knowledge base in such systems is the most signiﬁcant bottleneck in the maintenance of such systems, since the knowledge base needs to be expanded and updated as medical knowledge grows. Input The manner in which clinical information is entered into the CDSS (user interface) varies from system to system, but most diagnostic systems require the user to select terms from its specialized, controlled vocabulary. A. Spooner Comprehension of natural language has been an elusive goal in the development of CDSS.
JAMA 1998;280:1311–1316. 5. Oliveira, J. A shotgun wedding: business decision support meets clinical decision support. J Healthc Inf Manage 2002;16:28–33. 6. DeGruy KB. Healthcare applications of knowledge discovery in databases. J. Healthc Inf Manage 2000;14:59–69. 7. Perreault LE, Metzger JB. A pragmatic framework for understanding clinical decision support. In: Middleton, B, ed. Clinical Decision Support Systems. J Healthc Inf Manage 1999;13:5–21. 8. Metzger J, MacDonald K. Clinical decision support for the independent physician practice.
Again, this conclusion is obvious, but by representing the above syllogism using symbols, where the symbol Low-CO2 represents the state of abnormally low carbon dioxide and the symbol OVERVENTILATED represents the state of an over-ventilated patient, the syllogism looks more computerfriendly: Major Premise: Low-CO2 ⇒ OVERVENTILATED Minor Premise: Low-CO2 Conclusion: OVERVENTILATED Extending this example, suppose we have another statement in our CDSS that over-ventilation should cause a high rate alarm to sound (we can represent this by the symbol HIGH-RATE-ALARM), then we can construct the syllogism: Major Premise: Low-CO2 ⇒ OVERVENTILATED Minor Premise: Over-ventilated ⇒ HIGH-RATE-ALARM Conclusion: Low-CO2 ⇒ HIGH-RATE-ALARM Thus, we have generated a new rule for the system, where the intermediate state of over-ventilation is bypassed.