Journal of imaging informatics in medicine

Ovarian cancer remains one of the most challenging cancers to diagnose due to its non-specific symptoms, lack of reliable screening tests, and the complexity of detecting abnormalities. Accurate subtype classification is crucial for persona…

This study aimed to develop and validate a multimodal deep learning model that leverages 2D grayscale ultrasound (US) images alongside readily available clinical data to improve diagnostic performance for ovarian cancer (OC). A retrospectiv…

Endometrial carcinoma (EC) risk stratification prior to surgery is crucial for clinical treatment. In this study, we intend to evaluate the predictive value of radiomics models based on magnetic resonance imaging (MRI) for risk stratificati…

This study aimed to develop a model based on radiomics and deep learning features to predict the ablation rate in patients with adenomyosis undergoing high-intensity focused ultrasound (HIFU) therapy. A total of 119 patients with adenomyosi…