Radiomorphological signs and clinical severity of SARS-CoV-2 lineage B.1.1.7 [0.03%]
SARS-CoV-2变异株B.1.1.7的影像学表现及临床严重程度
Judit Simon,Kajetan Grodecki,Sebastian Cadet et al.
Judit Simon et al.
Objective: We aimed to assess the differences in the severity and chest-CT radiomorphological signs of SARS-CoV-2 B.1.1.7 and non-B.1.1.7 variants. Method...
The impact of altering participant MRI scanning position on back muscle volume measurements [0.03%]
改变受试者MRI扫描位置对背肌体积测量的影响
Salman Alharthi,Jude Meakin,Chris Wright et al.
Salman Alharthi et al.
Objectives: Muscle volume may reflect both strength and functional capability and hence is a parameter often measured to assess the effect of various interventions. The aim of the current study was to determine the sensit...
Arka Bhowmik,Sarah Eskreis-Winkler
Arka Bhowmik
Millions of breast imaging exams are performed each year in an effort to reduce the morbidity and mortality of breast cancer. Breast imaging exams are performed for cancer screening, diagnostic work-up of suspicious findings, evaluating ext...
Prospective multicentre analysis of the therapeutic approach and prognostic factors determining overall survival in elderly patients with non-small-cell lung carcinoma treated with curative intent [0.03%]
一项前瞻、多中心的研究：根治性治疗老年非小细胞肺癌患者的治疗模式和影响总体生存率的预后因素分析
Jon Cacicedo,Francisco Casquero,Arturo Navarro et al.
Jon Cacicedo et al.
Objective: To analyse patterns of treatment with curative intent commonly used in elderly patients with locally advanced non-small-cell lung carcinoma (NSCLC) and predictive factors of overall survival in routine clinical...
Evaluation of cancer outcome assessment using MRI: A review of deep-learning methods [0.03%]
基于MRI的癌症预后评估的深度学习方法研究
Yousef Mazaheri,Sunitha B Thakur,Almir Gv Bitencourt et al.
Yousef Mazaheri et al.
Accurate evaluation of tumor response to treatment is critical to allow personalized treatment regimens according to the predicted response and to support clinical trials investigating new therapeutic agents by providing them with an accura...
A qualitative study to explore opinions of Saudi Arabian radiologists concerning AI-based applications and their impact on the future of the radiology [0.03%]
一项定性研究：探索沙特放射科医师对基于人工智能的影像学应用及其对未来影响的观点
Walaa Alsharif,Abdulaziz Qurashi,Fadi Toonsi et al.
Walaa Alsharif et al.
Objective: The aim of this study was to explore opinions and views towards radiology AI among Saudi Arabian radiologists including both consultants and trainees. ...
Francesca Galati,Veronica Rizzo,Rubina Manuela Trimboli et al.
Francesca Galati et al.
Breast cancer (BC) is the most frequently diagnosed female invasive cancer in Western countries and the leading cause of cancer-related death worldwide. Nowadays, tumor heterogeneity is a well-known characteristic of BC, since it includes s...
Treatment outcomes of stereotactic ablative body radiotherapy on oligometastases from colorectal cancer: early results of a single institution service evaluation [0.03%]
立体定向体部放射治疗技术对结直肠癌寡转移瘤的疗效分析：一项单一机构服务评估的初步结果
Julie Duong,Adele Stewart-Lord,Prasana Nariyangadu et al.
Julie Duong et al.
Objective: Stereotactic ablative radiotherapy (SABR) has been suggested to be an effective non-invasive ablative therapy for oligometastases originated from colorectal cancer (CRC). This study aimed to report CRC oligomet...
Radiologist opinions regarding reporting incidental coronary and cardiac calcification on thoracic CT [0.03%]
放射科医师关于胸部CT上意外发现冠状动脉和心脏钙化的报告的意见
Michelle C Williams,Jonathan Weir-McCall,Alastair J Moss et al.
Michelle C Williams et al.
Objectives: Coronary and cardiac calcification are frequent incidental findings on non-gated thoracic computed tomography (CT). However, radiologist opinions and practices regarding the reporting of incidental calcificati...
Intubation and mortality prediction in hospitalized COVID-19 patients using a combination of convolutional neural network-based scoring of chest radiographs and clinical data [0.03%]
基于卷积神经网络的胸部X线评分与临床数据相结合对入住院COVID-19患者的插管和死亡率预测
Aileen O&#x;Shea,Matthew D Li,Nathaniel D Mercaldo et al.
Aileen O&#x;Shea et al.
Objective: To predict short-term outcomes in hospitalized COVID-19 patients using a model incorporating clinical variables with automated convolutional neural network (CNN) chest radiograph analysis. ...