Mobile Thalassaemia Diagnosis System Using Case-Based Reasoning

• Main Author: Mohammadnor Basri, Shafe
• Format: Thesis
• Language: English; English
• Published: 2005
• Subjects: QA71-90 Instruments and machines
• Online Access: http://etd.uum.edu.my/1268/1/MOHAMMADNOR_BASRI_B._SHAFE.pdf; http://etd.uum.edu.my/1268/2/1.MOHAMMADNOR_BASRI_B._SHAFE.pdf; http://etd.uum.edu.my/1268/

Nomadic nature of physicians restricts their access to digital information at times when it is needed. Thus, mobile device is seen is a plausible alternative. With the rapid development of mobile devices, its processing power also increases to cater to challenging computing task. Not only access to information, physician also needs to refer to past cases to make decision or diagnosis. Therefore, case-based reasoning, (CBR) a subset of AI technique is perceived to be useful in assisting physicians in making diagnosis. CBR compares new case with existing past cases in the case base and if there is similarity, the past solution is suggested as solution to the new case. This somewhat resembles human decision making. CBR provides justification and better explaination by depicting previous instance(s). As oppose to expert system, the task of knowledge elicitation turns into case histories gathering for CBR. Thalassaemia, a genetic blood disorder, is opted as the domain for this mobile CBR diagnosis system.