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Maximising Large Language Model Utility in Cardiovascular Care: A Practical Guide.

Authors :
Nolin-Lapalme A
Theriault-Lauzier P
Corbin D
Tastet O
Sharma A
Hussin JG
Kadoury S
Jiang R
Krahn AD
Gallo R
Avram R
Source :
The Canadian journal of cardiology [Can J Cardiol] 2024 Oct; Vol. 40 (10), pp. 1774-1787. Date of Electronic Publication: 2024 May 31.
Publication Year :
2024

Abstract

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.<br /> (Copyright © 2024 The Authors. Published by Elsevier Inc. All rights reserved.)

Details

Language :
English
ISSN :
1916-7075
Volume :
40
Issue :
10
Database :
MEDLINE
Journal :
The Canadian journal of cardiology
Publication Type :
Academic Journal
Accession number :
38825181
Full Text :
https://doi.org/10.1016/j.cjca.2024.05.024