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29-10-2024 | Artificial Intelligence | Public Health Policy (SS Virani and D Mahtta, Section Editors)

Artificial Intelligence Algorithms in Cardiovascular Medicine: An Attainable Promise to Improve Patient Outcomes or an Inaccessible Investment?

Authors: Patrícia Bota, Geerthy Thambiraj, Sandeep C. Bollepalli, Antonis A. Armoundas

Published in: Current Cardiology Reports

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Abstract

Purpose of Review

This opinion paper highlights the advancements in artificial intelligence (AI) technology for cardiovascular disease (CVD), presents best practices and transformative impacts, and addresses current concerns that must be resolved for broader adoption.

Recent Findings

With the evolution of digitization in data collection, large amounts of data have become available, surpassing the human capacity for processing and analysis, thus enabling the application of AI. These models can learn complex spatial and temporal patterns from large amounts of data, providing patient-specific outputs. These advantages have resulted, at the moment, in more than 900 AI-based devices being approved, today, by regulatory entities, for clinical use, with similar to improved performance and efficiency compared to traditional technologies. However, issues such as model generalization, bias, transparency, interpretability, accountability, and data privacy remain significant barriers for broad adoption of these technologies.

Summary

AI shows great promise in enhancing CVD care through more accurate and efficient approaches. Yet, widespread adoption is hindered by unresolved concerns of interested stakeholders. Addressing these challenges is crucial for fully integrating AI into clinical practice and shaping the future of CVD prevention, diagnosis and treatment.
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Metadata
Title
Artificial Intelligence Algorithms in Cardiovascular Medicine: An Attainable Promise to Improve Patient Outcomes or an Inaccessible Investment?
Authors
Patrícia Bota
Geerthy Thambiraj
Sandeep C. Bollepalli
Antonis A. Armoundas
Publication date
29-10-2024
Publisher
Springer US
Published in
Current Cardiology Reports
Print ISSN: 1523-3782
Electronic ISSN: 1534-3170
DOI
https://doi.org/10.1007/s11886-024-02146-y

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