Machine learning (ML), artificial neural networks (ANNs), and deep learning (DL) are all
topics that fall under the heading of artificial intelligence (AI) and have gained popularity in …

Artificial intelligence applications have shown success in different medical and health care
domains, and cardiac imaging is no exception. However, some machine learning models …

Explainable artificial intelligence (XAI) elucidates the decision-making process of complex AI
models and is important in building trust in model predictions. XAI explanations themselves …

Light‐sheet microscopy (LSM) enables us to strengthen the understanding of cardiac
development, injury, and regeneration in mammalian models. This emerging technique …

Despite ongoing efforts in cardiovascular research, the acquisition of high-resolution and
high-speed images for the purpose of assessing cardiac contraction remains challenging …

Artificial Intelligence is extensively applied in heartcare to analyze patient data, detect
anomalies, and provide personalized treatment recommendations, ultimately improving …

During the past decade, deep neural networks have become a popular tool in medical
image processing, particularly when grading cancer or abnormal tissues. Due to the scarcity …