Large language model-informed ECG dual attention network for heart failure risk prediction
Heart failure (HF) poses a significant public health challenge, with a rising global mortality
rate. Early detection and prevention of HF could significantly reduce its impact. We introduce …
rate. Early detection and prevention of HF could significantly reduce its impact. We introduce …
Whole heart 3d+ t representation learning through sparse 2d cardiac mr images
Abstract Cardiac Magnetic Resonance (CMR) imaging serves as the gold-standard for
evaluating cardiac morphology and function. Typically, a multi-view CMR stack, covering …
evaluating cardiac morphology and function. Typically, a multi-view CMR stack, covering …
Large-scale cross-modality pretrained model enhances cardiovascular state estimation and cardiomyopathy detection from electrocardiograms: An AI system …
Z Ding, Y Hu, Y Xu, C Zhao, Z Li, Y Mao, H Li… - arxiv preprint arxiv …, 2024 - arxiv.org
Cardiovascular diseases (CVDs) present significant challenges for early and accurate
diagnosis. While cardiac magnetic resonance imaging (CMR) is the gold standard for …
diagnosis. While cardiac magnetic resonance imaging (CMR) is the gold standard for …
Radiomics-guided Multimodal Self-attention Network for Predicting Pathological Complete Response in Breast MRI
Breast cancer is the most prevalent cancer among women and predicting pathologic
complete response (pCR) after anti-cancer treatment is crucial for patient prognosis and …
complete response (pCR) after anti-cancer treatment is crucial for patient prognosis and …
Mathematically-Grounded Multimodal Attention Network for Breast Cancer Prognosis
M Guo, Z Luo, J Liu, R Zhou - 2024 IEEE International …, 2024 - ieeexplore.ieee.org
Breast cancer is the most frequently diagnosed malignancy in women globally, underscoring
the necessity for precise prediction of pathologic complete response (pCR) to enhance …
the necessity for precise prediction of pathologic complete response (pCR) to enhance …
[PDF][PDF] Improving ECG Diagnosis of Left Ventricular Hypertrophy with Contrastive ECG-Echocardiogram Learning
Because existing ECG criteria for left ventricular hypertrophy (LVH) have poor sensitivity at
high specificity, we investigated whether deep learning (DL) could improve ECG-based LVH …
high specificity, we investigated whether deep learning (DL) could improve ECG-based LVH …