Tag: Artificial Intelligence

Approaches for Localizing the Origin of PVCs in the Outflow Tract: Future Perspectives and Challenges

Announcing a new article publication for Cardiovascular Innovations and Applications journal. Idiopathic ventricular arrhythmias (IVAs) are a type of arrhythmias with focal origins. The locations of most such arrhythmias have been identified and confirmed. In cases in which pharmacological treatment is ineffective or limited, radiofrequency catheter ablation is a therapeutic option whose success rate largely depends on accurate IVA localization.

The current standard approach for localizing the origin of IVAs involves comparing the normal electrocardiogram (ECG) with the characteristic ECG of the arrhythmia. This comparison includes analysis of parameters such as the QRS wave polarity in different leads, QRS duration, R/S ratio, and S-R difference in precordial leads.

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Clinical Application of Artificial Intelligence in the Diagnosis, Prediction, and Classification of Coronary Heart Disease

Announcing a new article publication for Cardiovascular Innovations and Applications journal. Coronary heart disease (CHD), the most common cause of mortality globally, poses a formidable challenge to modern healthcare systems. Artificial intelligence (AI) is playing an increasingly important role in multiple diagnostic applications of CHD, by facilitating early intervention and personalized treatment. This article describes the state of the art and provides clinicians with updated insights into the transformative potential of AI to enhance CHD detection.

AI can be used to increase diagnostic and prognostic accuracy. However, its reliance on homogeneous numerical data might potentially lead to misdiagnoses and unnecessary radiation exposure in diagnosing CHD.

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Artificial Intelligence Solutions for Cardiovascular Disease Detection and Management in Women

Announcing a new article publication for Cardiovascular Innovations and Applications journal. Artificial intelligence (AI) is a method of data analysis that enables machines to learn patterns from datasets and make predictions. With advances in computer chip technology for data processing and the increasing availability of big data, AI can be leveraged to improve cardiovascular care for women – an often understudied and undertreated population. The authors of this article briefly discuss the potential benefits of AI-based solutions in cardiovascular care for women and also highlight inadvertent drawbacks to the use of AI and novel digital technologies in women.

https://www.scienceopen.com/hosted-document?doi=10.15212/CVIA.2023.0024

CVIA is available on the ScienceOpen platform and at Cardiovascular Innovations and Applications. Submissions may be made using ScholarOne Manuscripts. There are no author submission or article processing fees. Cardiovascular Innovations and Applications is indexed in the EMBASE, EBSCO, ESCI, OCLC, Primo Central (Ex Libris), Sherpa Romeo, NISC (National Information Services Corporation), DOAJ, Index Copernicus, Research4Life and Ulrich’s web Databases. Follow CVIA on Twitter @CVIA_Journal; or Facebook.

Wendy Tatiana Garzon-Siatoya, Andrea Carolina Morales-Lara and Demilade Adedinsewo. Artificial Intelligence Solutions for Cardiovascular Disease Detection and Management in Women: Promise and Perils. CVIA. 2023. Vol. 8(1). DOI: 10.15212/CVIA.2023.0024

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