Artificial Intelligence for Cardiovascular Care—Part 1: Advances: JACC Review Topic of the Week
P Elias, SS Jain, T Poterucha, M Randazzo… - Journal of the American …, 2024 - jacc.org
Recent artificial intelligence (AI) advancements in cardiovascular care offer potential
enhancements in diagnosis, treatment, and outcomes. Innovations to date focus on …
enhancements in diagnosis, treatment, and outcomes. Innovations to date focus on …
[HTML][HTML] Atrial fibrillation and stroke: State-of-the-art and future directions
S Elsheikh, A Hill, G Irving, GYH Lip… - Current problems in …, 2024 - Elsevier
Atrial fibrillation (AF) and stroke remain a major cause of morbidity and mortality. The two
conditions shared common co-morbidities and risk factors. AF-related strokes are associated …
conditions shared common co-morbidities and risk factors. AF-related strokes are associated …
Practical intelligent diagnostic algorithm for wearable 12-lead ECG via self-supervised learning on large-scale dataset
J Lai, H Tan, J Wang, L Ji, J Guo, B Han, Y Shi… - Nature …, 2023 - nature.com
Cardiovascular disease is a major global public health problem, and intelligent diagnostic
approaches play an increasingly important role in the analysis of electrocardiograms …
approaches play an increasingly important role in the analysis of electrocardiograms …
The digital journey: 25 years of digital development in electrophysiology from an Europace perspective
Aims Over the past 25 years there has been a substantial development in the field of digital
electrophysiology (EP) and in parallel a substantial increase in publications on digital …
electrophysiology (EP) and in parallel a substantial increase in publications on digital …
Artificial intelligence in cardiovascular diseases: diagnostic and therapeutic perspectives
X Sun, Y Yin, Q Yang, T Huo - European Journal of Medical Research, 2023 - Springer
Artificial intelligence (AI), the technique of extracting information from complex database
using sophisticated computer algorithms, has incorporated itself in medical field. AI …
using sophisticated computer algorithms, has incorporated itself in medical field. AI …
[HTML][HTML] State-of-the-art deep learning methods on electrocardiogram data: systematic review
Background Electrocardiogram (ECG) is one of the most common noninvasive diagnostic
tools that can provide useful information regarding a patient's health status. Deep learning …
tools that can provide useful information regarding a patient's health status. Deep learning …
Prediction of atrial fibrillation from at-home single-lead ECG signals without arrhythmias
Early identification of atrial fibrillation (AF) can reduce the risk of stroke, heart failure, and
other serious cardiovascular outcomes. However, paroxysmal AF may not be detected even …
other serious cardiovascular outcomes. However, paroxysmal AF may not be detected even …
Deep learning of electrocardiograms in sinus rhythm from US veterans to predict atrial fibrillation
Importance Early detection of atrial fibrillation (AF) may help prevent adverse cardiovascular
events such as stroke. Deep learning applied to electrocardiograms (ECGs) has been …
events such as stroke. Deep learning applied to electrocardiograms (ECGs) has been …
Use of Artificial Intelligence in Improving Outcomes in Heart Disease: A Scientific Statement From the American Heart Association
A major focus of academia, industry, and global governmental agencies is to develop and
apply artificial intelligence and other advanced analytical tools to transform health care …
apply artificial intelligence and other advanced analytical tools to transform health care …
A review of evaluation approaches for explainable AI with applications in cardiology
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 …
models and is important in building trust in model predictions. XAI explanations themselves …