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[HTML][HTML] Artificial intelligence in cardiology—a narrative review of current status
G Koulaouzidis, T Jadczyk, DK Iakovidis… - Journal of Clinical …, 2022 - mdpi.com
Artificial intelligence (AI) is an integral part of clinical decision support systems (CDSS),
offering methods to approximate human reasoning and computationally infer decisions …
offering methods to approximate human reasoning and computationally infer decisions …
Machine learning in arrhythmia and electrophysiology
Machine learning (ML), a branch of artificial intelligence, where machines learn from big
data, is at the crest of a technological wave of change swee** society. Cardiovascular …
data, is at the crest of a technological wave of change swee** society. Cardiovascular …
Computational models of atrial fibrillation: Achievements, challenges, and perspectives for improving clinical care
Despite significant advances in its detection, understanding and management, atrial
fibrillation (AF) remains a highly prevalent cardiac arrhythmia with a major impact on …
fibrillation (AF) remains a highly prevalent cardiac arrhythmia with a major impact on …
Critical appraisal of technologies to assess electrical activity during atrial fibrillation: A position paper from the European heart rhythm association and European …
We aim to provide a critical appraisal of basic concepts underlying signal recording and
processing technologies applied for (i) atrial fibrillation (AF) map** to unravel AF …
processing technologies applied for (i) atrial fibrillation (AF) map** to unravel AF …
Applications of artificial intelligence in cardiology. The future is already here
There is currently no other hot topic like the ability of current technology to develop
capabilities similar to those of human beings, even in medicine. This ability to simulate the …
capabilities similar to those of human beings, even in medicine. This ability to simulate the …
The association between diabetes mellitus and atrial fibrillation: clinical and mechanistic insights
A number of clinical studies have reported that diabetes mellitus (DM) is an independent risk
factor for Atrial fibrillation (AF). After adjustment for other known risk factors including age …
factor for Atrial fibrillation (AF). After adjustment for other known risk factors including age …
Machine learning–enabled multimodal fusion of intra-atrial and body surface signals in prediction of atrial fibrillation ablation outcomes
S Tang, O Razeghi, R Kapoor… - Circulation …, 2022 - ahajournals.org
Background: Machine learning is a promising approach to personalize atrial fibrillation
management strategies for patients after catheter ablation. Prior atrial fibrillation ablation …
management strategies for patients after catheter ablation. Prior atrial fibrillation ablation …
How machine learning is impacting research in atrial fibrillation: implications for risk prediction and future management
There has been an exponential growth of artificial intelligence (AI) and machine learning
(ML) publications aimed at advancing our understanding of atrial fibrillation (AF), which has …
(ML) publications aimed at advancing our understanding of atrial fibrillation (AF), which has …
Preprocedure application of machine learning and mechanistic simulations predicts likelihood of paroxysmal atrial fibrillation recurrence following pulmonary vein …
Background: Pulmonary vein isolation (PVI) is an effective treatment strategy for patients
with atrial fibrillation (AF), but many experience AF recurrence and require repeat ablation …
with atrial fibrillation (AF), but many experience AF recurrence and require repeat ablation …
Machine-learning to stratify diabetic patients using novel cardiac biomarkers and integrative genomics
Background Diabetes mellitus is a chronic disease that impacts an increasing percentage of
people each year. Among its comorbidities, diabetics are two to four times more likely to …
people each year. Among its comorbidities, diabetics are two to four times more likely to …