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A tutorial on case based reasoning
Marijuana Grower's Handbook Ed Rosenthal. Homegrown Tea Cassie Liversidge. Workbenches, Revised Christopher Schwarz. The cases can have attributes from a vocabulary, which can be defined with the constraint of global commitments so that the attributes can be shared and interpreted in a distributed setting. We have implemented a knowledge sharing protocol with common ontology as the repository of exchange vocabulary for knowledge sources with different Universe of Discourses UOD. We have developed a shell for tailored application development in different domains.
We have illustrated effectiveness of our approach by developing a travel planning and a help desk application.
International Scholarly Research Notices
The cause of the viral hepatitis disease is a virus, and initially, it can appear like a cold. Most of those suffering hepatitis kinds C and B have no symptoms. Some of these patients show symptoms of viral infection in nature such as, fatigue, stomach ache, muscle pain, and nausea, and loss of appetite. But symptoms of liver failure occur in advanced cases including swelling of the abdomen and limbs, jaundice, and digestive bleedings.
A lot of researchers have recently used computational intelligence in diagnosing different diseases.
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Among these methods, neural networks are most widely used. Different kinds of neural networks with various specifications have been used in diagnosing diseases [ 1 ].
- Soft computing in case based reasoning?
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- A tutorial on case based reasoning.
A lot of researches have been done through neural networks and fuzzy system for diagnosis of B hepatitis disease [ 2 , 3 ]. Methods with better classification accuracy will provide more sufficient information to identify the potential patients and to improve the diagnosis accuracy. Meta-heuristic algorithms like genetic algorithms, particle swarm optimizations, fish swarm optimization, and Tabu Search and data mining tools neural network and decision tree have been applied in this area.
Aside from other traditional classification problems, medical data classifications are further applied in disease diagnosis. Therefore, patients or doctors not only need to know the answer classification result , they also need to know the symptoms that derive this answer.
Case-Based Reasoning Resources
As for other clinical diagnosis problems, classification systems have been used for hepatitis disease diagnosis problem. When the studies in the literature related with this classification application are examined, it can be seen that a great variety of methods were used which reached high Classification accuracies using the dataset taken from UCI machine learning repository. Table 1 is a review of different methods for diagnosis of hepatitis disease.
Different methods of neural networks and their combination with other methods have achieved good results. Liao [ 4 ] investigated of a hybrid CBR method for failure mechanisms identification. Hua Tan et al.
Saridakis and Dentsoras [ 7 ] introduced a case-based design with a soft computing system to evaluate the parametric design of an oscillating conveyor. Hybrid CBR has also been used in the medical planning and application areas. Hsu and Ho [ 9 ] combined the CBR, NN, fuzzy theory, and induction theory together to facilitate multiple-disease diagnosis and the learning of new adaptation knowledge. Ahn and Kim [ 11 ] combined the CBR with genetic algorithms to evaluate cytological features derived from a digital scan of breast fine needle aspirate FNA slides.
In addition, hybrid CBRs have been used in the financial forecasting areas. Chun and Park [ 17 ] devised a regression CBR for financial forecasting, which applies different weights to independent variables before finding similar cases.
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