BACKGROUND: It is difficult to predict normal-sized lymph node metastasis (LNM) in cervical cancer clinically. We aimed to investigate the feasibility of using deep learning (DL) nomogram based on readout segmentation of long variable echo-trains dif...
BACKGROUND: Several studies have used artificial intelligence (AI) to analyze cytology images, but AI has yet to be adopted in clinical practice. The objective of this study was to demonstrate the accuracy of AI-based image analysis for thyroid fine-...
Journal of vascular and interventional radiology : JVIR
Dec 16, 2022
PURPOSE: To investigate the utility and generalizability of deep learning subtraction angiography (DLSA) for generating synthetic digital subtraction angiography (DSA) images without misalignment artifacts.
BACKGROUND: To compare the clinical efficacy of unilateral unstable sacral fractures (USFs) involving the lumbosacral region treated with and without robot-aided triangular osteosynthesis (TOS).
OBJECTIVE: To investigate performance of 1-mm, sharp kernel, low-dose chest computed tomography (LDCT) for coronary artery calcium scoring (CACS) using deep learning (DL)-based denoising technique.
BACKGROUND: Predominant traditional approaches for most patients who have advanced-stage oral cancer with transcervical incision lines left irreversible scars. To address this, surgeons have continuously refined minimally invasive surgery (MIS) techn...
PURPOSE: To compare a deep learning model with a radiomics model in differentiating high-grade (LR-3, LR-4, LR-5) liver imaging reporting and data system (LI-RADS) liver tumors from low-grade (LR-1, LR-2) LI-RADS tumors based on the contrast-enhanced...
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