A novel model for predicting fatty liver disease by means of an artificial neural network

作     者：Yi-Shu Chen Dan Chen Chao Shen Ming Chen Chao-Hui Jin Cheng-Fu Xu Chao-Hui Yu You-Ming Li 

作者机构：Department of GastroenterologyThe First Affiliated HospitalCollege of MedicineZhejiang UniversityHangzhouZhejiangP.R.China Health Management CenterThe First Affiliated HospitalCollege of MedicineZhejiang UniversityHangzhouZhejiangP.R.China Hithink Royal Flush Information Network Co.LtdHangzhouZhejiangP.R.China 

出 版 物：《Gastroenterology Report》 (胃肠病学报道（英文）)

年 卷 期：2021年第9卷第1期

页      面：31-37,I0001,I0002页

核心收录：

学科分类：1002[医学-临床医学] 100201[医学-内科学(含：心血管病、血液病、呼吸系病、消化系病、内分泌与代谢病、肾病、风湿病、传染病)] 10[医学] 

基　　金：supported by the National Key R&D Program of China[2017YFC0908900] 

主　　题：artificial neural network diagnostic model fatty liver disease Fatty Liver Index Hepatic Steatosis Index uric acid 

摘      要：Background:The artificial neural network(ANN)emerged recently as a potent diagnostic tool,especially for complicated systemic *** study aimed to establish a diagnostic model for the recognition of fatty liver disease(FLD)by virtue of the ***:A total of 7,396 pairs of gender-and age-matched subjects who underwent health check-ups at the First Affiliated Hospital,College of Medicine,Zhejiang University(Hangzhou,China)were enrolled to establish the ANN *** available in health check-up reports were utilized as potential input *** performance of our model was evaluated through a receiver-operating characteristic(ROC)curve *** outcome measures included diagnostic accuracy,sensitivity,specificity,Cohen’s k coefficient,Brier score,and Hosmer-Lemeshow *** Fatty Liver Index(FLI)and the Hepatic Steatosis Index(HSI),retrained using our training-group data with its original designated input variables,were used as comparisons in the capability of FLD ***:Eight variables(age,gender,body mass index,alanine aminotransferase,aspartate aminotransferase,uric acid,total triglyceride,and fasting plasma glucose)were eventually adopted as input nodes of the ANN *** applying a cut-off point of 0.51,the area under ROC curves of our ANN model in predicting FLD in the testing group was 0.908[95%confidence interval(CI),0.901-0.915]—significantly higher(P0.05)than that of the FLI model(0.881,95%CI,0.872-0.891)and that of the HSI model(0.885;95%CI,0.877-0.893).Our ANN model exhibited higher diagnostic accuracy,better concordance with ultrasonography results,and superior capability of calibration than the FLI model and the HSI ***:Our ANN system showed good capability in the diagnosis of *** is anticipated that our ANN model will be of both clinical and epidemiological use in the future.