Area of research
Reproductive Medicine · Obstetrics and Gynecology
Research interest
Research interests include Medicine, Artificial intelligence, Ultrasound, Computer science, Deep learning, and Receiver operating characteristic.
Deep learning based on ultrasound images to predict platinum resistance in patients with epithelial ovarian cancer
Multimodal Deep Learning Based on Ultrasound Images and Clinical Data for Better Ovarian Cancer Diagnosis
Discriminative diagnosis of ovarian endometriosis cysts and benign mucinous cystadenomas based on the ConvNeXt algorithm
A Study on Automatic O-RADS Classification of Sonograms of Ovarian Adnexal Lesions Based on Deep Convolutional Neural Networks
Exploratory study on the enhancement of O-RADS application effectiveness for novice ultrasonographers via deep learning
Prediction of benign and malignant ovarian tumors using Resnet34 on ultrasound images
Prediction model of adnexal masses with complex ultrasound morphology
An Intelligent Ovarian Ultrasound Image Generation Algorithm based on Generative Adversarial Networks
Iodine nutrition and prevalence of sonographic thyroid findings in adults in the Heilongjiang Province, China
Ultrasound related risk factors for assessing short-term efficacy of radio frequency ablation for uterine fibroids