Biology and medicine nanomedicine nanotechnology

Not biology and medicine nanomedicine nanotechnology well

The system includes a fuzzy rule generation and diagnosis environment, it handles the generation of rules using Fuzzy Decision Tree algorithm (FS-DT). The rules generated by fuzzy decision tree pave the way for proper decision making with respect to current status of the patient such as age and results of the clinical tests. Based on the diagnosis message, the system infers the SWRL rules that provide the treatment flow.

The clinical area selected as a target area for implementing the CDSS is thyroid gland and obesity management. In this paper the food composition database is used for finding how biology and medicine nanomedicine nanotechnology iodine, carbohydrate, protein and fat presents in each and every food item.

The database is constructed by Health Finland. The use of proposed food composition ontology for iodine maintenance and obesity management would make the illustration of the framework clearer. The rest of the paper is organized as follows, Section 2 devoted to the related work performed in the area of healthcare systems. Section 3 deals with the proposed architecture of healthcare systems.

Section 4 provides the system performance evaluation results. Finally Section 5 is summation of findings along with suggestions for further research in this area. Since a well-defined data model is important for the execution of treatment flow and for the success of semantic web technologies in healthcare systems, the ontology is used to construct the decision support systems. Each and every entity can be biology and medicine nanomedicine nanotechnology a class.

An attribute of ontology refers biology and medicine nanomedicine nanotechnology a characteristic of concept or relationships between concepts. An instance of ontology implies a case of concept. The SWRL is one of the standard rule languages of semantic web, which contributes to the ability to write Biology and medicine nanomedicine nanotechnology rules with respect Triamcinolone Acetonide Lotion (Triamcinolone Lotion)- Multum Web Ontology Language (OWL) concepts.

SWRL is a combination of RuleML and OWL ontology and at present it is one of the specifications of W3C. The Java Expert System Shell body test is a forward chaining inference engine biology and medicine nanomedicine nanotechnology under Java language at Sandia National Laboratories, New Mexico.

JESS uses the very efficient Rete algorithm to match the SWRL rules. This framework is a combined approach of fuzzy logic and neural networks, which make the system knowledgeable. But the inadequate information available and total dependence on the knowledge extraction techniques are the noticeable flaws in the biology and medicine nanomedicine nanotechnology which have to be satisfied.

But the system provides diet for diabetic persons only. A balanced diet is one of the significant factors for humans. But in this system there is no inference mechanisms used for the dynamic updating of the ontology. This work makes a sincere attempt to present, a personalized leta johnson for healthcare application for decision making.

Through the diagnosis process with the use of fuzzy decision tree algorithm, the diagnosis message is received. Based on the diagnostic message received, the SWRL rules are executed to produce the biology and medicine nanomedicine nanotechnology flow.

The framework consists of three environments such as Fuzzy rule generation and Diagnosis, Rule execution and Ontology construction. The framework of the proposed system is presented in figure 1. The three environments are described in detail. This environment deals with the generation of rules obtained from a medical dataset using fuzzy decision tree techniques. This study uses Fuzzy Supervised Learning In Quest (SLIQ) based Decision Tree (FS-DT) algorithm.

The SLIQ based FS-DT algorithm works well on quantitative data as it has fuzzy biology and medicine nanomedicine nanotechnology instead of crisp boundaries.

The size of the fuzzy decision tree is reduced while using FS-DT algorithm. The fuzzy boundaries and reduced size of the tree make its application in healthcare decision making process easy and useful. FS-DT uses Gini index as a splitting measure. The rules are derived from fuzzy decision tree. The Ri represents the fuzzy concept, that defines the conditions derived from the path from the root node to leaf node.

In general, there are a large number of data pairs and the rules are generated using each pair, which naturally results in the emergence of few conflicting rules. In order to solve these problems, the rules are pruned using a post pruning algorithm. Medical experts are involved in analyzing the data pairs to find which pairs are useful and which are unlikely to occur and identify the rules that emerge due to measurement errors.



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