cardiovascular disease
PulseAugur coverage of cardiovascular disease — every cluster mentioning cardiovascular disease across labs, papers, and developer communities, ranked by signal.
4 day(s) with sentiment data
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New study maps human adipocyte development using single-cell RNA sequencing
Researchers have utilized single-cell RNA sequencing to map the developmental path of adipocytes in human adipose tissue. The study identified 15 distinct cell clusters and 7 transitional states, revealing dynamic diffe…
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AI tool predicts heart disease from EKGs
An AI tool has been developed that can analyze electrocardiograms (EKGs) to predict the likelihood of developing structural heart disease. This technology aims to provide early warnings for cardiovascular issues by inte…
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AI's data bottleneck, healthcare applications, and agentic automation advance · 4 sources tracked
A report indicates that generative AI projects may exceed their budgets by 2028, suggesting that data, rather than model performance, is the primary bottleneck for Finance AI applications. Separately, AI is being develo…
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New Framework Aligns CT and EHR Data for Improved Time-to-Event Prediction
Researchers have developed a new framework for cross-modal representation alignment to improve time-to-event (TTE) prediction using both CT imaging and longitudinal electronic health records (EHR). This foundation model…
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New Radar Model Improves Cardiac Sensing Accuracy
Researchers have developed a novel pre-training model called TriDP-PTM for radar-based cardiac sensing. This model addresses the trade-off between distortion and perception in non-contact monitoring by employing a three…
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AI model predicts cardiovascular disease progression using ECG data
Researchers have developed a novel artificial intelligence model designed to predict the progression of cardiovascular disease following a myocardial infarction. This model leverages self-supervised learning on unlabele…
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Federated Learning advances balance privacy, utility, and fairness
Researchers are exploring advanced techniques to enhance privacy in Federated Learning (FL), a method where models train on decentralized data. One study compares Differential Privacy (DP) and Homomorphic Encryption (HE…