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Critical appraisal of artificial intelligence-based prediction models for cardiovascular disease

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The medical field has seen a rapid increase in the development of artificial intelligence (AI)-based prediction models. With the introduction of such AI-based prediction model tools and software in cardiovascular patient care, the cardiovascular researcher and healthcare professional are challenged to understand the opportunities as well as the limitations of the AI-based predictions. In this article, we present 12 critical questions for cardiovascular health professionals to ask when confronted with an AI-based prediction model. We aim to support medical professionals to distinguish the AI-based prediction models that can add value to patient care from the AI that does not. Listen to the audio abstract of this contribution. Artificial intelligence (AI) and its subdiscipline machine learning are receiving increasing attention throughout medicine, including cardiovascular medicine.1,2 Proponents promise AI will change the way medicine and healthcare is practiced, by making use of technological advancements that allow for collection of increasingly detailed and diverse data and the ever-increasing computational ability to analyse and combine such data. An important part of these promises is the development and implementation of more accurate clinical prediction models (algorithms, tools, or rules, from here onwards simply referred to as prediction models) to improve--or according to some advocates, even revolutionize--screening, diagnosis, and prognostication of diseases.


Startup Bay Labs Uses AI for Heart Disease Diagnosis NVIDIA Blog

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And humans need health screenings, especially for the heart. That's because heart disease is the leading cause of death worldwide. With deep learning, heart disease diagnosis is becoming easier and more accessible -- which in turn can improve treatment and patient outcomes. Echocardiograms -- ultrasound tests that generate images of the heart -- are used to detect and manage heart disease cases. An echo, as it's commonly called, is also used as an assessment tool for specific populations, such as chemotherapy patients, because of their increased risk of heart failure.


Future of Cardiology Will Be Defined by Digital, Mobile Advances

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The future of cardiovascular care will be transformed by advances in artificial intelligence, digital health technology and mobile devices as a means to prevent and treat heart disease, according to several articles published June 4, 2018 in a Journal of the American College of Cardiology Focus Seminar on the Future Technology of Cardiovascular Care. As the type and breadth of data available to cardiologists and the cardiovascular care team continues to grow more sophisticated, physicians are increasingly being asked to provide more rapid and personalized interpretations of data to their patients. One solution to providing this level of personalized medicine efficiently is artificial intelligence, also known as machine learning. In the review article Artificial Intelligence in Cardiology,[1] researchers analyze select applications of artificial intelligence in cardiology and identify how the specialty could incorporate more artificial intelligence in the future to enhance the capabilities and experiences of clinicians and patients. "(Artificial intelligence) has clear potential to enhance every stage of patient care -- from research and discovery, to diagnosis, to selection of therapy," said Joel Dudley, Ph.D., senior author of the review and director of the Next Generation Healthcare Institute at Mount Sinai.


AI Accurately Predicts If – And When – Someone Could Die of Sudden Cardiac Arrest

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A new artificial intelligence-based approach can predict, significantly more accurately than a doctor, if and when a patient could die of cardiac arrest. The technology, built on raw images of patient's diseased hearts and patient backgrounds, stands to revolutionize clinical decision making and increase survival from sudden and lethal cardiac arrhythmias, one of medicine's deadliest and most puzzling conditions. The work, led by Johns Hopkins University researchers, is detailed on April 7, 2022, in Nature Cardiovascular Research. "Sudden cardiac death caused by arrhythmia accounts for as many as 20 percent of all deaths worldwide and we know little about why it's happening or how to tell who's at risk," said senior author Natalia Trayanova, the Murray B. Sachs professor of Biomedical Engineering and Medicine. "There are patients who may be at low risk of sudden cardiac death getting defibrillators that they might not need and then there are high-risk patients that aren't getting the treatment they need and could die in the prime of their life. What our algorithm can do is determine who is at risk for cardiac death and when it will occur, allowing doctors to decide exactly what needs to be done."


AI predicts if -- and when -- someone will have cardiac arrest

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It detected high risk in the heart circled in red. A new artificial intelligence-based approach can predict, significantly more accurately than a doctor, if and when a patient could die of cardiac arrest. The technology, built on raw images of patient's diseased hearts and patient backgrounds, stands to revolutionize clinical decision making and increase survival from sudden and lethal cardiac arrhythmias, one of medicine's deadliest and most puzzling conditions. The work, led by Johns Hopkins University researchers, is detailed today in Nature Cardiovascular Research. "Sudden cardiac death caused by arrhythmia accounts for as many as 20 percent of all deaths worldwide and we know little about why it's happening or how to tell who's at risk," said senior author Natalia Trayanova, the Murray B. Sachs professor of Biomedical Engineering and Medicine.