Joining Data Mining with a Knowledge-Based System for Efficient Personalized Speech Therapy

Author(s):  
Mirela Danubianu
Author(s):  
Nilamadhab Mishra ◽  
Johny Melese Samuel

The eye is the most important sensory organ of vision function. But some eye diseases can lead to vision loss, so it is important to identify and treat eye disease as early as possible. Eye care professionals can help protect their patients from vision loss or blindness by recognizing common eye diseases and recommending for an eye exam. Eye diseases with early detection, treatment, and appropriate follow-up care, vision loss, and blindness from eye disease can be prevented or delayed. In this study, rule-based eye disease identification and advising the knowledge-based system are projected. The projected system is targeting using hidden knowledge extracted by employing the extraction algorithm of data mining. To identify the best prediction model for the diagnosis of eye disease, four experiments for four classification algorithms were performed. Finally, the researchers decided to use the rules of the J48 pruned classification algorithm for further use in the development of a knowledge base of KBS because it exhibited better performance with a 98.5% evaluation result.


2020 ◽  
Vol 30 (1) ◽  
Author(s):  
Kedir Eyasu ◽  
Worku Jimma ◽  
Takele Tadesse

BACKGROUND: Diabetes is a disease that affects the body’s ability to produce or use insulin. A total of 425 million people are suffering from diabetes in the world. Of this, more than 16 million people live in the Africa Region, which is estimated to be around 41 million by 2045. The main objective of this study was to design and develop a prototype knowledge-based system using data mining techniques for diagnosis and treatment of diabetes.METHODS: For this study, experimental research design was employed, and the researchers used domain expert knowledge as a supplement of data mining techniques whereby three classification algorithms in WEKA; namely J48, PART and JRip were used, and finally the researchers decided to use the results of J48 classification algorithm. Ultimate Visual basic studio 2013 (Vb.net) was used to store knowledge and as front side of prototype. Common lisp prolog (Clisp) was used for obtained knowledge back end coding.RESULTS: Using a decision tree algorithm; namely J48, 2512 (95.1515%) of the instances were classified correctly, and 128 (4.8485 %) were classified incorrectly. The second most performing model was generated by JRip Classier. This model scored the 94.7348% accuracy on the general data to classify the status of diabetic patient datasets. It classified the 2501 instances of the records correctly.CONCLUSION: The J48 model was the best performing model with the best accuracy of results. 


2014 ◽  
Vol 1 (1) ◽  
pp. 339-342
Author(s):  
Mirela Danubianu ◽  
Dragos Mircea Danubianu

AbstractSpeech therapy can be viewed as a business in logopaedic area that aims to offer services for correcting language. A proper treatment of speech impairments ensures improved efficiency of therapy, so, in order to do that, a therapist must continuously learn how to adjust its therapy methods to patient's characteristics. Using Information and Communication Technology in this area allowed collecting a lot of data regarding various aspects of treatment. These data can be used for a data mining process in order to find useful and usable patterns and models which help therapists to improve its specific education. Clustering, classification or association rules can provide unexpected information which help to complete therapist's knowledge and to adapt the therapy to patient's needs.


1986 ◽  
Author(s):  
Richard H. Brown ◽  
Jonathan K. Millen ◽  
Ethan A. Scarl

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