Qualitative American Heart Association plot of late gadolinium enhancement with mortality and ventricular arrhythmia prediction using artificial intelligence [0.03%]
人工智能预测心源性死亡和室性心律失常的晚期钆增强定性美国心脏协会图
Ebraham Alskaf,Cian M Scannell,Avan Suinesiaputra et al.
Ebraham Alskaf et al.
Background: The prognostic value of late gadolinium enhancement (LGE) in cardiac magnetic resonance (CMR) imaging is well-established. However, the direct relationship between image pixels and outcomes remains poorly unde...
Hybrid artificial intelligence outcome prediction using features extraction from stress perfusion cardiac magnetic resonance images and electronic health records [0.03%]
基于应力灌注心脏磁共振图像和电子健康记录的特征提取的混合人工智能结果预测
Ebraham Alskaf,Richard Crawley,Cian M Scannell et al.
Ebraham Alskaf et al.
Background: Prediction of clinical outcomes in coronary artery disease (CAD) has been conventionally achieved using clinical risk factors. The relationship between imaging features and outcome is still not well understood...
Efficient labelling for efficient deep learning: the benefit of a multiple-image-ranking method to generate high volume training data applied to ventricular slice level classification in cardiac MRI [0.03%]
一种多重图像排序生成训练数据的方法在心脏磁共振成像心室切片分类中的应用研究
Sameer Zaman,Kavitha Vimalesvaran,James P Howard et al.
Sameer Zaman et al.
Background: Getting the most value from expert clinicians' limited labelling time is a major challenge for artificial intelligence (AI) development in clinical imaging. We present a novel method for ground-truth labelling...
Deep learning applications in coronary anatomy imaging: a systematic review and meta-analysis [0.03%]
基于深度学习的冠状动脉解剖影像研究：系统回顾与元分析
Ebraham Alskaf,Utkarsh Dutta,Cian M Scannell et al.
Ebraham Alskaf et al.
Background: The application of deep learning on medical imaging is growing in prevalence in the recent literature. One of the most studied areas is coronary artery disease (CAD). Imaging of coronary artery anatomy is fund...
Machine learning can accelerate discovery and application of cyber-molecular cancer diagnostics [0.03%]
机器学习可以加速网络分子癌症诊断的发现和应用
David S Campo,Yury Khudyakov
David S Campo
Improving ultrasound video classification: an evaluation of novel deep learning methods in echocardiography [0.03%]
改进超声视频分类：心超声心动图中新型深度学习方法的评估
James P Howard,Jeremy Tan,Matthew J Shun-Shin et al.
James P Howard et al.
Echocardiography is the commonest medical ultrasound examination, but automated interpretation is challenging and hinges on correct recognition of the 'view' (imaging plane and orientation). Current state-of-the-art methods for identifying ...
Simone L Van Es,Anant Madabhushi
Simone L Van Es