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. 2023 Dec 4;19(10):e798-e801.
doi: 10.4244/EIJ-D-23-00461.

Towards AI-assisted cardiology: a reflection on the performance and limitations of using large language models in clinical decision-making

Adil Salihu  1 , Mehdi Ali Gadiri  2 , Ioannis Skalidis  1 , David Meier  1 , Denise Auberson  1 , Annick Fournier  3 , Romain Fournier  4 , Dorina Thanou  5   6 , Emmanuel Abbé  5   7 , Olivier Muller  1 , Stephane Fournier  1
Affiliations

Towards AI-assisted cardiology: a reflection on the performance and limitations of using large language models in clinical decision-making

Adil Salihu et al. EuroIntervention. .
No abstract available

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Conflict of interest statement

The authors have no conflicts of interest to declare.

Figures

Figure 1
Figure 1. First clinical vignette submitted to ChatGPT.
EuroSCORE: European System for Cardiac Operative Risk Evaluation; LAD: left anterior descending; NYHA: New York Heart Association; STS: Society of Thoracic Surgeons
Figure 2
Figure 2. Second clinical vignette submitted to ChatGPT.
CAD: coronary artery disease; CT: computed tomography; LAD: left anterior descending; NYHA: New York Heart Association; PCI: percutaneous coronary intervention; PET: positron emission tomography
See this image and copyright information in PMC

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