Download e-book for kindle: Dealing with Medical Knowledge: Computers in Clinical by E. Carson, T. Deutsch, E. Ludwig

By E. Carson, T. Deutsch, E. Ludwig

ISBN-10: 1475799519

ISBN-13: 9781475799514

ISBN-10: 1475799535

ISBN-13: 9781475799538

In a scientific and transparent demeanour, the authors speak about the issues linked to medical determination making and discover the present easy methods to remedy them. during this monograph, they research the result of combining the classical keep an eye on method process with the symbolic methods which were significant to advancements in man made intelligence. good illustrated with case experiences, this quantity will turn out to be a useful source to approach scientists, engineers, computing device scientists, and individuals of the clinical community.

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Extra resources for Dealing with Medical Knowledge: Computers in Clinical Decision Making

Sample text

We shall discuss them in turn. 1. Frames A frame is a data structure that represents a complex object, situation, or stereotype with the concept's name and various properties arranged in slot-filler pairs (Minsky, 1975). Frames are usually linked together to form a frame tree or network in which the different frames can inherit values in their slots from each other. The slot is an element in a frame that represents a property of the object. The filler is a value that occupies a slot in a frame, often represented as a pointer to another frame.

1992). The overall method for controlling the sequence of rule evocation is termed the control strategy that is used by the inference engine. Access to rules can vary from a very simple scheme, in which the rules are used in a preestablished order, to more complex dynamic activation sequences, in which the choice may depend on current facts in the database. A predetermined order of activation of rules may imply selecting a rule first because it is used most frequently or because it has the highest certainty factor.

The probability of the concomitant occurrence of any number of events, E I , E 2 , ••• , En is called the joint probability and written as P(Ep E 2, ... , En)' Conditional probability, p(EIF), refers to the occurrence of event E provided that event F is known to occur. 5) 26 Chapter 3 Generally, if FI' F 2 , we obtain: P(E) ••• ,F'; are mutually exclusive and exhaustive events, = P(E ,F1) + P(E ,F2) + . . 6) which is the summation principle for joint probabilities. There are several suggestions for handling uncertainty in another way.

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Dealing with Medical Knowledge: Computers in Clinical Decision Making by E. Carson, T. Deutsch, E. Ludwig


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