An Intelligent Appointment System Based on Support Vector Machine
碩士 === 國立屏東商業技術學院 === 資訊管理系(所) === 98 === Taiwan implements all the people health insurance already many years. Before family doctor system not yet universalization, sickness mostly custom by depends on own symptom feeling directly to the hospital seeing a doctor or by the telephone and the network...
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| Format: | Others |
| Language: | zh-TW |
| Published: |
2010
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| Online Access: | http://ndltd.ncl.edu.tw/handle/73809040162481292175 |
| Summary: | 碩士 === 國立屏東商業技術學院 === 資訊管理系(所) === 98 === Taiwan implements all the people health insurance already many years. Before family doctor system not yet universalization, sickness mostly custom by depends on own symptom feeling directly to the hospital seeing a doctor or by the telephone and the network registration. Insufficient hangs the wrong branch because of the populace universal medical service knowledge to leave frequently, creates the medical resources waste or the delay condition. This research in view of this question to adopt Support Vector Machine(SVM) of Artificial Neural Network to establishes a forecast classifies expert system to search doctor branch . It will correct distribution disease of the common symptom. This system may assist sickness to be able to choose the suitable branch seeing a doctor. Avoids hanging the wrong branch to cause of repeatedly to go see a doctor either the error diagnostic causes life and the health and the medical resources waste or the harm sickness. In order to appraise result of this diagnosis system. We also respectively use Back-propagation Network(BPN) regarded as compares to the standard. The experimental result showed that Support Vector Machine(SVM) is better than
Back-propagation Network(BPN).
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