F. Wu, H.-P. Sun, and Y.-T. Wang (Taiwan)
Appointment system, symptom, neural network, hospital information system, closed staff hospital.
For avoiding getting in lines, most hospitals provide convenient ways for patients to make an appointment easily. A web-based appointment system can facilitate the patients to make an appointment. However, the medical knowledge of the patients is limited. They can not always make a correct decision about which department they should visit. This paper establishes an on-line consulting system. It gets the symptoms and the concerns from the patients and then provides them the advices about which department the patients should visit. The system contains the knowledge base. The system first tries to match the input symptoms with the contents in the knowledge base. If the input symptoms do not exactly match the data in the knowledge base, a backward-propagation neural network is used to perform the classification of the possible departments. With the advices, the patient has higher satisfaction and better outcomes.
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