About this Research Topic
Prevalence of heart failure (HF) is projected to increase by 46% from 2012 to 2030, affecting more than 8 million people, 18 years of age or older. Despite advances in therapy, HF continues to be a major cause of morbidity and mortality worldwide with a lifetime risk at age 40 years of approximately 20%.
A wide variety of drugs, devices, and procedures are available to improve survival and functional class in patients with HF. Patients with mild to moderately decompensated HF can usually be stabilized with medical treatment. For those who are extremely ill and unstable, various mechanical cardiac support devices can be used to attempt stabilization or as a bridge to transplantation.
New device-based treatments are being developed to treat specific pathways in patients with HF. Artificial Intelligence (AI) performs human intelligence-dependant tasks using tools such as machine learning (ML), and its subtype deep learning. AI has incorporated itself in the field of cardiovascular medicine and is increasingly employed to revolutionize diagnosis, treatment, risk prediction, clinical care, and drug discovery. ML offers flexibility and scalability in assimilating and evaluating large amounts of complex healthcare data. Unlike the traditional statistical methods that focus on inference, ML methods concentrate on prediction by finding patterns in rich and unwieldy data.
This Research Topic will search for new therapies that may impact the quality of life and/or survival of patients with heart failure. This encompasses new drugs or new devices, with the help of contemporary technologies involving AI and ML for continuous improvement.
A wide variety of drugs, devices, and procedures are available to improve survival and functional class in patients with HF. Patients with mild to moderately decompensated HF can usually be stabilized with medical treatment. For those who are extremely ill and unstable, various mechanical cardiac support devices can be used to attempt stabilization or as a bridge to transplantation.
New device-based treatments are being developed to treat specific pathways in patients with HF. Artificial Intelligence (AI) performs human intelligence-dependant tasks using tools such as machine learning (ML), and its subtype deep learning. AI has incorporated itself in the field of cardiovascular medicine and is increasingly employed to revolutionize diagnosis, treatment, risk prediction, clinical care, and drug discovery. ML offers flexibility and scalability in assimilating and evaluating large amounts of complex healthcare data. Unlike the traditional statistical methods that focus on inference, ML methods concentrate on prediction by finding patterns in rich and unwieldy data.
This Research Topic will search for new therapies that may impact the quality of life and/or survival of patients with heart failure. This encompasses new drugs or new devices, with the help of contemporary technologies involving AI and ML for continuous improvement.
Keywords: heart failure, artificial intelligence, machine learning
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