Non-invasive biopsy diagnosis of diabetic kidney disease via deep learning applied to retinal images: a population-based study [0.03%]
基于人群的利用深度学习分析视网膜图像诊断糖尿病肾脏疾病的非侵入性活检法研究
Ziyao Meng,Zhouyu Guan,Shujie Yu et al.
Ziyao Meng et al.
Background: Improving the accessibility of screening diabetic kidney disease (DKD) and differentiating isolated diabetic nephropathy from non-diabetic kidney disease (NDKD) are two major challenges in the field of diabete...
Utilising the Benefit Risk Assessment of Vaccines (BRAVE) toolkit to evaluate the benefits and risks of Vaxzevria in the EU: a population-based study [0.03%]
利用疫苗获益风险评估（BRAVE）工具包评价欧盟地区AZD1222(Oxford-AstraZeneca/Vaxzevria)新冠肺炎疫苗的获益和风险：基于人口的研究
Hector Gonzalez Dorta,Johan Verbeeck,Jonas Crevecoeur et al.
Hector Gonzalez Dorta et al.
Background: Several COVID-19 vaccines have been licensed. To support the assessment of safety signals, we developed a toolkit to support COVID-19 vaccine monitoring and benefit-risk assessment. We aim to show the applicat...
Generating evidence to support the role of AI in diabetic eye screening: considerations from the UK National Screening Committee [0.03%]
生成证据以支持AI在糖尿病眼筛查中的作用：来自英国国家筛查委员会的考虑事项
Trystan Macdonald,Zhivko Zhelev,Xiaoxuan Liu et al.
Trystan Macdonald et al.
Screening for diabetic retinopathy has been shown to reduce the risk of sight loss in people with diabetes, because of early detection and treatment of sight-threatening disease. There is long-standing interest in the possibility of automat...
Weighing the benefits and risks of collecting race and ethnicity data in clinical settings for medical artificial intelligence [0.03%]
在临床环境中收集种族和族裔数据以用于医学人工智能的利弊权衡
Amelia Fiske,Sarah Blacker,Lester Darryl Geneviève et al.
Amelia Fiske et al.
Many countries around the world do not collect race and ethnicity data in clinical settings. Without such identified data, it is difficult to identify biases in the training data or output of a given artificial intelligence (AI) algorithm, ...
Electrocardiogram-based deep learning to predict left ventricular systolic dysfunction in paediatric and adult congenital heart disease in the USA: a multicentre modelling study [0.03%]
在美国基于心电图的深度学习预测儿科和成人先天性心脏病的左心室收缩功能障碍：一项多中心建模研究
Joshua Mayourian,Ivor B Asztalos,Amr El-Bokl et al.
Joshua Mayourian et al.
Background: Left ventricular systolic dysfunction (LVSD) is independently associated with cardiovascular events in patients with congenital heart disease. Although artificial intelligence-enhanced electrocardiogram (AI-EC...
Multicenter Study
The Lancet. Digital health. 2025 Apr;7(4):e264-e274. DOI:10.1016/j.landig.2025.01.001 2025
Snapshot artificial intelligence-determination of ejection fraction from a single frame still image: a multi-institutional, retrospective model development and validation study [0.03%]
快照人工智能-从单帧静态图像确定射血分数：一项多机构回顾性模型开发和验证研究
Jeffrey G Malins,D M Anisuzzaman,John I Jackson et al.
Jeffrey G Malins et al.
Background: Artificial intelligence (AI) is poised to transform point-of-care practice by providing rapid snapshots of cardiac functioning. Although previous AI models have been developed to estimate left ventricular ejec...
Multicenter Study
The Lancet. Digital health. 2025 Apr;7(4):e255-e263. DOI:10.1016/j.landig.2025.02.003 2025
Beyond the social media ban [0.03%]
超越社交媒体禁令
The Lancet Digital Health
The Lancet Digital Health