Prediction of postoperative complications of pediatric cataract patients using data mining

Journal of Translational Medicine

Kai Zhang¹  Xiyang Liu¹  Jiewei Jiang¹  Lin Liu¹  Liming Wang¹  Xiaojing Zhou²  Shuai Wang³  Wangting Li⁴ 

[1] School of Computer Science and Technology, Xidian University;School of Computer Science, Northwestern Polytechnical University;School of Software, Xidian University;State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University;

关键词: Random forest;    Naïve Bayesian;    Association rules mining;    Genetic feature selection;    Medical decision making system;   

DOI  :  10.1186/s12967-018-1758-2

来源: DOAJ

【 摘 要 】

Abstract Background The common treatment for pediatric cataracts is to replace the cloudy lens with an artificial one. However, patients may suffer complications (severe lens proliferation into the visual axis and abnormal high intraocular pressure; SLPVA and AHIP) within 1 year after surgery and factors causing these complications are unknown. Methods Apriori algorithm is employed to find association rules related to complications. We use random forest (RF) and Naïve Bayesian (NB) to predict the complications with datasets preprocessed by SMOTE (synthetic minority oversampling technique). Genetic feature selection is exploited to find real features related to complications. Results Average classification accuracies in three binary classification problems are over 75%. Second, the relationship between the classification performance and the number of random forest tree is studied. Results show except for gender and age at surgery (AS); other attributes are related to complications. Except for the secondary IOL placement, operation mode, AS and area of cataracts; other attributes are related to SLPVA. Except for the gender, operation mode, and laterality; other attributes are related to the AHIP. Next, the association rules related to the complications are mined out. Then additional 50 data were used to test the performance of RF and NB, both of then obtained the accuracies of over 65% for three classification problems. Finally, we developed a webserver to assist doctors. Conclusions The postoperative complications of pediatric cataracts patients can be predicted. Then the factors related to the complications are found. Finally, the association rules that is about the complications can provide reference to doctors.

【 授权许可】

Unknown