Abstract
There are many scholars trying to diagnose the disease using intelligent computers and computer networks, in order to meet the growing needs of patients. Most of them diagnose disease based on the patients’ symptoms, the collected medical data and some algorithms, but they can’t figure out the probability of every possible disease. This paper presents an assessment model by using AHP method which can evaluate these possible diseases. The assessment model can calculate the correlation between each disease and every possible symptom by the collected medical data. According to the correlation and the actual severity of symptoms, we can evaluate the exact probability of every possible disease.
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© 2012 Springer-Verlag Berlin Heidelberg
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Li, Q., Zhang, L., Chu, H. (2012). An AHP-Based Assessment Model for Clinical Diagnosis and Decision. In: Lei, J., Wang, F.L., Deng, H., Miao, D. (eds) Artificial Intelligence and Computational Intelligence. AICI 2012. Lecture Notes in Computer Science(), vol 7530. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-33478-8_34
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DOI: https://doi.org/10.1007/978-3-642-33478-8_34
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-33477-1
Online ISBN: 978-3-642-33478-8
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