An artificial intelligence model for electrocardiogram detection of occlusion myocardial infarction: a retrospective study to reduce false-positive cath lab activations [0.03%]
一种心电图检测急性心肌梗死的人工智能模型：减少错误启动导管实验室的回顾性研究
Benjamin L Cooper,Evan A Genova,Carrie A Bakunas et al.
Benjamin L Cooper et al.
Aims: Existing ST-segment elevation myocardial infarction (STEMI) alert pathways that rely on traditional STEMI criteria perform suboptimally. We aimed to evaluate the diagnostic performance of an artificial intelligence ...
Retraction of: Validation of a popular consumer-grade cuffless blood pressure device for continuous 24 h monitoring [0.03%]
撤稿：一种流行的消费者无袖带血压设备的验证以实现连续24小时监测
[This retracts the article DOI: 10.1093/ehjdh/ztaf044.]. © The Author(s) 2026. Published by Oxford University Press on behalf of the European Society of...
Multimodal deep learning for acute myocardial infarction detection from 12-lead electrocardiogram: a multi-centre study with cross-hospital validation [0.03%]
基于12导联心电图的急性心肌梗死多模态深度学习检测方法：多中心研究及跨医院验证
Vibha Gupta,Lukas Hilgendorf,Erik Andersson et al.
Vibha Gupta et al.
Aims: Acute myocardial infarction (AMI) remains a leading global cause of mortality, where timely diagnosis is critical to enable early intervention. The 12-lead electrocardiogram (ECG) is a critical tool for AMI detectio...
Impact of remote monitoring on well-being, therapeutic adherence, and organ damage evaluation in hypertensive patients: the PROSIT study [0.03%]
远程监测对高血压患者健康、治疗依丛和靶器官损害评估的影响：PROSIT研究
Marialuisa S Marozzi,Vanessa Desantis,Francesco Corvasce et al.
Marialuisa S Marozzi et al.
Aims: The PROSIT (Patient-Reported Outcomes and Smart-Imaging in Telecardiology) study aimed to evaluate the feasibility and potential clinical impact of remote patient monitoring in hypertension management, focusing on m...
Machine learning-enabled systematic review on coded healthcare data in heart failure research [0.03%]
基于机器学习的心力衰竭研究中的编码医疗保健数据的系统评价
Asgher Champsi,Karin T Slater,Simrat Gill et al.
Asgher Champsi et al.
Aims: Coded healthcare data are now commonly used in clinical research. This study aimed to assess the transparency of reporting within heart failure studies and employ machine learning to facilitate larger-scale evaluati...
Effectiveness of fully immersive virtual reality-based simulation training on objective knowledge acquisition in acute coronary syndrome/ST-elevation myocardial infarction emergency management: a pre-post-intervention study [0.03%]
基于全浸入式虚拟现实的模拟培训在急性冠状动脉综合征/ ST段抬高型心肌梗死急救管理客观知识获取方面的有效性：一项预试验后干预研究
Jonas Einloft,Philipp Russ,Simon Bedenbender et al.
Jonas Einloft et al.
Aims: Effective management of emergencies, particularly acute coronary syndrome (ACS), demands rapid, guideline-based interventions to optimize outcomes. However, many medical students and young professionals report feeli...
A fully automated explainable predictive model for diagnosing pre-capillary and post-capillary pulmonary hypertension on routine unenhanced CT: results from the ASPIRE registry [0.03%]
一项关于ASPIRE登记的常规未增强CT上诊断前毛细血管和后毛细血管肺动脉高压的全自动可解释预测模型的结果研究报告
Turki Nasser Alnasser,Alireza Hokmabadi,Elliot W Checkley et al.
Turki Nasser Alnasser et al.
Aims: Unenhanced chest CT is frequently used to assess lung malignancy and parenchymal disease. Harnessing CT data to quantify cardiac and vascular structures has the potential to improve the diagnosis of heart failure an...
Unsupervised machine learning analysis to enhance risk stratification in patients with asymptomatic aortic stenosis [0.03%]
无症状主动脉瓣狭窄患者的非监督机器学习分析以增强风险分层
Marie-Ange Fleury,Louis Ohl,Lionel Tastet et al.
Marie-Ange Fleury et al.
Aims: There is a lack of studies investigating the pathophysiologic and phenotypic distinctiveness of aortic stenosis (AS). This heterogeneity has important implications for identifying optimal intervention timing and pot...
Non-invasive analysis of pump parameter responses to orthostatic transitions in patients with fully magnetically levitated left ventricular assist devices [0.03%]
完全磁悬浮左心室辅助装置患者直立位转换泵参数的无创分析
Lukas Ruoff,Gregor Widhalm,Michael Röhrich et al.
Lukas Ruoff et al.
Aims: Despite the excellent clinical outcomes of the HeartMate 3 (HM3) left ventricular assist device, the current pump monitoring limits in-depth pump data analysis. This study investigated HM3 pump parameters collected ...
From haemodynamics to kidney risk: AI-based early prediction validated in general and burn ICU populations [0.03%]
从血流动力学到肾脏风险：基于人工智能的早期预测在普通ICU和烧伤ICU人群中的验证
Louis Boutin,Fedi Kadri,Arij Chaftar et al.
Louis Boutin et al.
Aims: Acute kidney injury (AKI) is a frequent and severe complication in critically ill patients with cardiovascular instability. Current risk scores rely on delayed renal biomarkers such as serum creatinine (sCr) and blo...