MR Imaging Features for Predicting Microvascular Invasion of Hepatocellular Carcinoma: Is Radiomics Truly Helpful? [0.03%]
影像组学在预测肝细胞癌微血管侵犯的价值和意义
Xuan Wang,Liang Zhu
Xuan Wang
Multi-machine Learning Model Based on Habitat Subregions for Outcome Prediction in Adenomyosis Treated by Uterine Artery Embolization [0.03%]
基于栖息地亚区域的多机器学习模型在子宫动脉栓塞治疗子宫腺肌症预后预测中的应用
Wentao Jin,Shijia Wang,Tianpin Wang et al.
Wentao Jin et al.
Rationale and objectives: To establish and validate a predictive multi-machine learning model for the long-term efficacy of uterine artery embolization (UAE) in the treatment of adenomyosis based on habitat subregions. ...
Development and validation of an 18F-FDG PET/CT-based radiomics nomogram for predicting the prognosis of patients with esophageal squamous cell carcinoma [0.03%]
开发并验证一种基于18F-FDG PET/CT的影像组学预测食管鳞癌患者预后的列线图模型
Jiahui Huang,Tiannv Li,Lijun Tang et al.
Jiahui Huang et al.
Rationale and objectives: The aim of this study was to develop and validate a nomogram, integrating clinical factors and radiomics features, capable of predicting overall survival (OS) in patients diagnosed with esophagea...
Predicting lymphovascular invasion in non-small cell lung cancer using deep convolutional neural networks on preoperative chest CT [0.03%]
基于术前胸部CT的深度卷积神经网络在非小细胞肺癌淋巴血管侵犯中的预测价值研究
Jian Wang,Yang Yang,Zongyu Xie et al.
Jian Wang et al.
Rationale and objectives: Lymphovascular invasion (LVI) plays a significant role in precise treatments of non-small cell lung cancer (NSCLC). This study aims to build a non-invasive LVI prediction diagnosis model by combi...
Evaluation of ChatGPT-Generated Educational Patient Pamphlets for Common Interventional Radiology Procedures [0.03%]
评估用于常见介入放射学程序的教育性患者手册，这些手册由ChatGPT生成
Soheil Kooraki,Melina Hosseiny,Mohamamd H Jalili et al.
Soheil Kooraki et al.
Rationale and objectives: This study aimed to evaluate the accuracy and reliability of educational patient pamphlets created by ChatGPT, a large language model, for common interventional radiology (IR) procedures. ...
Radiology Under Pressure: The Challenge of Burnout in Residents and a Call for Action [0.03%]
积劳成疾：放射学培训医师面临的压力及应对措施
Javier Alejandro Lamprea Ardila,Sergio Alejandro Castellanos Sánchez,Luis Fernando Pulido Cadavid et al.
Javier Alejandro Lamprea Ardila et al.
Radiomic Prediction of CCND1 Expression Levels and Prognosis in Low-grade Glioma Based on Magnetic Resonance Imaging [0.03%]
基于磁共振成像的低级别胶质瘤CCND1表达量和预后的影像组学预测模型研究
Kun Zhao,Hui Zhang,Jianyang Lin et al.
Kun Zhao et al.
Ojectives: Low-grade glioma (LGG) is associated with increased mortality owing to recrudescence and the tendency for malignant transformation. Therefore, it is imperative to discover novel prognostic biomarkers as existin...
Predicting Left Ventricular Adverse Remodeling After Transcatheter Aortic Valve Replacement: A Radiomics Approach [0.03%]
基于影像组学预测经导管主动脉瓣置换术后左心室重塑
Tingli Yan,Lujing Wang,Xiaoyi Chen et al.
Tingli Yan et al.
Rationale and objectives: To develop a radiomics model based on cardiac computed tomography (CT) for predicting left ventricular adverse remodeling (LVAR) in patients with severe aortic stenosis (AS) who underwent transca...
Predicting cardiovascular risk stratification in apparently healthy population by using noninvasive ultrafast ultrasound imaging [0.03%]
基于无创快速超声影像的心血管风险分层预测研究
Zhengqiu Zhu,Lingshan Chen,Bixiao Shen et al.
Zhengqiu Zhu et al.
Background: To investigate the association between cardiovascular risk estimated using the Framingham Risk Score (FRS) and carotid stiffening determined using ultrafast pulse wave velocity (ufPWV) measurements in apparent...
Talal Mourad,Omer A Awan
Talal Mourad