Abstract:
Objective
To get better accuracy, microscopic review rules of urine sediments were built based on a decision tree approach.
Methods
A total of 2000 urine samples were examined using UF-1000i, Urisys-2400, and RS 2003 urine sediment workstation, respectively. Positive and negative samples were defined, and both the training and testing sets were set up. Finally, a decision tree approach was employed to construct classifiers for screening urine samples.
Results
Using the decision tree method, we obtained a sensitivity of 85.0%, a specificity of 96.4% and a total review rate of 25.0% on the testing set, showing the acceptable sensitivity and lower total review rate comparing with the existing method.
Conclusion
An algorithm based on the decision tree for building review criteria can be available, which is valuable and a supplement for other microscopic review rules.
Key words:
Microscopic review rules,
Decision tree,
Urinalysis, UF-1000i
Yuan CAO, Yan-qun WANG, Zi-han SUN, Li SUN, Ning HAN, Xiu-min DU, Li-xin KONG, Ruixia QI, Cheng-jin HU. Construction of microscopy review rules based on UF-1000i using decision tree approach[J]. Chinese Journal of Kidney Disease Investigation(Electronic Edition), 2013, 02(01): 38-41.