Maximising Large Language Model Utility in Cardiovascular Care: A Practical Guide Article Swipe
YOU?
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· 2024
· Open Access
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· DOI: https://doi.org/10.1016/j.cjca.2024.05.024
Large language models (LLMs) have emerged as powerful tools in artificial intelligence, demonstrating remarkable capabilities in natural language processing and generation. In this article, we explore the potential applications of LLMs in enhancing cardiovascular care and research. We discuss how LLMs can be used to simplify complex medical information, improve patient-physician communication, and automate tasks such as summarising medical articles and extracting key information. In addition, we highlight the role of LLMs in categorising and analysing unstructured data, such as medical notes and test results, which could revolutionise data handling and interpretation in cardiovascular research. However, we also emphasise the limitations and challenges associated with LLMs, including potential biases, reasoning opacity, and the need for rigourous validation in medical contexts. This review provides a practical guide for cardiovascular professionals to understand and harness the power of LLMs while navigating their limitations. We conclude by discussing the future directions and implications of LLMs in transforming cardiovascular care and research.
Related Topics
- Type
- review
- Language
- en
- Landing Page
- https://doi.org/10.1016/j.cjca.2024.05.024
- http://onlinecjc.ca/article/S0828282X2400415X/pdf
- OA Status
- hybrid
- Cited By
- 16
- References
- 65
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4399207734
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https://openalex.org/W4399207734Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1016/j.cjca.2024.05.024Digital Object Identifier
- Title
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Maximising Large Language Model Utility in Cardiovascular Care: A Practical GuideWork title
- Type
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reviewOpenAlex work type
- Language
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enPrimary language
- Publication year
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2024Year of publication
- Publication date
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2024-05-31Full publication date if available
- Authors
-
Alexis Nolin-Lapalme, Pascal Thériault-Lauzier, Denis Corbin, Olivier Tastet, Abhinav Sharma, Julie Hussin, Samuel Kadoury, River Jiang, Andrew D. Krahn, Richard L. Gallo, Robert AvramList of authors in order
- Landing page
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https://doi.org/10.1016/j.cjca.2024.05.024Publisher landing page
- PDF URL
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https://onlinecjc.ca/article/S0828282X2400415X/pdfDirect link to full text PDF
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YesWhether a free full text is available
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hybridOpen access status per OpenAlex
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https://onlinecjc.ca/article/S0828282X2400415X/pdfDirect OA link when available
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Medicine, Interpretation (philosophy), Computer science, Programming languageTop concepts (fields/topics) attached by OpenAlex
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16Total citation count in OpenAlex
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2025: 14, 2024: 2Per-year citation counts (last 5 years)
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65Number of works referenced by this work
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10Other works algorithmically related by OpenAlex
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