Predicting Disease Activity for Biologic Selection in Rheumatoid Arthritis
Keyword(s):
In this article, we implemented a regression model and conducted experiments for predicting disease activity using data from 1929 rheumatoid arthritis patients to assist in the selection of biologics for rheumatoid arthritis. On modelling, the missing variables in the data were completed by three different methods, mean value, self-organizing map and random value. Experimental results showed that the prediction error of the regression model was large regardless of the missing completion method, making it difficult to predict the prognosis of rheumatoid arthritis patients.
2021 ◽
Vol 80
(Suppl 1)
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pp. 1083.2-1084
2010 ◽
Vol 25
(1)
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pp. 27-47
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2009 ◽
Vol 137
(3-4)
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pp. 171-174
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2020 ◽
Vol 79
(Suppl 1)
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pp. 1409.2-1409
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2021 ◽
Vol 9
(B)
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pp. 411-416
2021 ◽
Vol 80
(Suppl 1)
◽
pp. 448.2-448
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