Recent research demonstrates that deep learning could facilitate opportunistic screening and allow for earlier prevention and management of patients with cardiovascular disease. Learn more about the present opportunities.
The concept of a Smart Hospital is evolving in 2021. Read how new hospital construction can anticipate climate change, decentralization of care delivery, and advances in medical science.
Deep learning-based CT-FFR has demonstrated potential in improving the diagnosis of patients with coronary artery disease. Learn more about how deep learning-based CT-FFR can help improve patient outcomes in this introductory guide.
A new study conducted by researchers at the First Affiliated Hospital of Jinan University demonstrates that deep learning-based CT-FFR (DL-CTFFR) can reduce the need for invasive coronary angiography (ICA) and improve outcomes in patients with stable coronary artery disease (CAD).
Evidence is building in support of a coronary CTA-first strategy for evaluating patients with stable coronary artery disease. Learn more about the current evidence, guidelines, and recommendations.
Researchers at Fuwai Hospital conducted a retrospective study to evaluate the performance of Keya Medical’s deep learning-based CT-FFR product in detecting hemodynamic changes in stenosis.
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