The paper delineates neutral networks broadly and describes their purpose primarily in medicine. As per research, neural networks dig deeper and shape the functional aspects of computational features of the brain. The paper goes further and touches on the applications of neural networks particularly in medicine. Also, the text elucidates the notion of inference in general terms in addition to the concept of the Bayesian network model. In this specific part, it explains the theory that forms the basis of Bayesian algorithm and highlights some of its applications in clinical decision support systems. Moreover, the paper clarifies the notion of decision trees and supports it with an illustration which can help in breast cancer diagnosis. Furthermore, in the paper is an inference engine which can be utilized when diagnosing simple pyelonephritis with all symptoms mentioned. In conclusion is the definition of some unique set of related objects which describes uncomplicated pyelonephritis in a patient. The set is illustrated as per the textbook.
Keywords: Neural Networks, decision trees, inference, Bayesian network model
Neural networks are estimation models established on the mathematical paradigm that opposed to old computing have an operation and structure that is similar to a brain. They are referred to connectionist systems, adaptive systems or parallel distributed …
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