Nuttaya Pattamapaspong,Thanat Kanthawang,Wilfred C G Peh et al.
Nuttaya Pattamapaspong et al.
Tuberculosis (TB) remains the leading cause of death from a single infectious agent globally, despite being a potentially curable disease. This disease typically affects the lungs but may involve many extrapulmonary sites, especially in pat...
Accuracy of an artificial intelligence-enabled diagnostic assistance device in recognizing normal chest radiographs: a service evaluation [0.03%]
一种人工智能诊断辅助设备在识别正常胸部X线片方面的准确性：一项服务评估研究
Amrita Kumar,Puja Patel,Dennis Robert et al.
Amrita Kumar et al.
Objectives: Artificial intelligence (AI) enabled devices may be able to optimize radiologists' productivity by identifying normal and abnormal chest X-rays (CXRs) for triaging. In this service evaluation, we investigated ...
Patient, tumour, and dosimetric factors influencing survival in non-small cell lung cancer patients treated with stereotactic ablative body radiotherapy [0.03%]
立体定向体部放射治疗影响非小细胞肺癌患者生存的因素分析
Minal Padden-Modi,Yevhen Spivak,Ian Gleeson et al.
Minal Padden-Modi et al.
Objectives: We aimed to analyse clinical outcomes of peripheral, early-stage non-small cell lung cancer (NSCLC) patients treated with stereotactic ablative body radiotherapy (SABR), and evaluate potential patient, tumour,...
Dual-energy CT: Impact of detecting bone marrow oedema in occult trauma in the Emergency [0.03%]
双能量CT在急诊隐匿性创伤骨髓水肿检测中的应用价值研究
Muhammad Israr Ahmad,Lulu Liu,Adnan Sheikh et al.
Muhammad Israr Ahmad et al.
Dual-energy computed tomography (DECT) is an advanced imaging technique that acquires data using two distinct X-ray energy spectra, typically at 80 and 140 kVp, to differentiate materials based on their atomic number and electron density. T...
Establishing the size and configuration of the imaging support workforce: a census of national workforce data in England [0.03%]
建立影像支持型工作人员的规模和配置：英格兰全国劳动力数据普查
Julie Nightingale,Sarah Etty,Beverley Snaith et al.
Julie Nightingale et al.
Objectives: The imaging support workforce is a key enabler in unlocking imaging capacity and capability, yet no evidence exists of the workforce size and configuration. This research provides the first comprehensive analy...
Emergency department referrals for CT imaging of extremity soft tissue infection: before and during the COVID-19 pandemic [0.03%]
新冠疫情前后的急诊CT扫描四肢软组织感染会诊情况分析
Andrew Nanapragasam,Lawrence M White
Andrew Nanapragasam
Objectives: To evaluate the incidence and spectrum of findings in patients referred for CT imaging of extremity soft tissue infection in the adult emergency department (ED) setting before and during the COVID-19 pandemic....
Augmented reality and radiology: visual enhancement or monopolized mirage [0.03%]
增强现实与放射学：视觉提升还是垄断幻影？
Matthew Christie
Matthew Christie
Augmented reality (AR) exists on a spectrum, a mixed reality hybrid of virtual projections onto real surroundings. Superimposing conventional medical imaging onto the living patient offers vast potential for radiology, potentially revolutio...
Complex abdominal aortic aneurysms: a review of radiological and clinical assessment, endovascular interventions, and current evidence of management outcomes [0.03%]
复杂腹主动脉瘤的影像和临床评估、血管内治疗及当前管理效果证据综述
Girija Agarwal,Mohamad Hamady
Girija Agarwal
Endovascular aortic aneurysm repair (EVAR) is an established approach to treating abdominal aortic aneurysms, however, challenges arise when the aneurysm involves visceral branches with insufficient normal segment of the aorta to provide an...
Three-dimensional dose prediction based on deep convolutional neural networks for brain cancer in CyberKnife: accurate beam modelling of homogeneous tissue [0.03%]
基于深度卷积神经网络的Cyber刀治疗脑肿瘤三维剂量预测：均匀组织下的精确射束建模
Yuchao Miao,Ruigang Ge,Chuanbin Xie et al.
Yuchao Miao et al.
Objectives: Accurate beam modelling is essential for dose calculation in stereotactic radiation therapy (SRT), such as CyberKnife treatment. However, the present deep learning methods only involve patient anatomical image...
Advancing radiology practice and research: harnessing the potential of large language models amidst imperfections [0.03%]
借助大型语言模型推动放射学实践和研究：在不完美中发现潜力
Eyal Klang,Lee Alper,Vera Sorin et al.
Eyal Klang et al.
Large language models (LLMs) are transforming the field of natural language processing (NLP). These models offer opportunities for radiologists to make a meaningful impact in their field. NLP is a part of artificial intelligence (AI) that u...