Hao Sun, Yuan Zhong, Lixian Liao, Jujiang Wu, Hongwu Xu, Junqiang Ma
Obesity and hypertension mediate the effect of education on deep intracerebral hemorrhage: A Mendelian randomization study
Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association
objective study develop deep learning model using convnext algorithm effectively differentiate ovarian endometriosis cysts oec benign mucinous cystadenomas mc analyzing ultrasound images performance model diagnostic differentiation two conditions also evaluated retrospective analysis conducted oec mc patients sought medical attention fourth affiliated hospital harbin medical university august 2018 may 2023 diagnosis established based postoperative pathology characteristics aspirated fluid guided ultrasound serving gold standard ultrasound images collected subjected screening preprocessing procedures data set randomly divided training validation testing sets ratio 532 transfer learning utilized determine initial weights convnext deep learning algorithm adjusted retraining algorithm using training validation ultrasound images establish new deep learning model weights yielded highest accuracy selected evaluate diagnostic performance model using validation set receiver operating characteristic roc curves generated area curve auc calculated additionally sensitivity specificity positive predictive value negative predictive value positive likelihood ratio negative likelihood ratio odds ratio calculated decision curve analysis dca curves plotted study included 786 ultrasound images 184 patients diagnosed either oec mc deep learning model achieved auc 090 95 ci 085095 accurately distinguishing two conditions sensitivity 90 95 ci 84 95 specificity 90 95 ci 77 97 positive predictive value 96 95 ci 91 99 negative predictive value 77 95 ci 63 88 positive likelihood ratio 927 95 ci 3652356 negative likelihood ratio 011 95 ci 006019 dca curve demonstrated practical clinical utility model deep learning model developed using convnext algorithm exhibits high accuracy 90 distinguishing oec mc model demonstrates excellent diagnostic performance clinical utility providing novel approach clinical differentiation two conditions