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Editorial
. 2024 Jun 18;13(12):e035815.
doi: 10.1161/JAHA.124.035815. Epub 2024 Jun 15.

Principles of Artificial Intellgence for Medicine

Oguz Akbilgic  1
Affiliations
Editorial

Principles of Artificial Intellgence for Medicine

Oguz Akbilgic. J Am Heart Assoc. .
No abstract available

Keywords: Editorials; congenital; heart defects; machine learning; oximetry.

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Figures

Figure 1
Figure 1. Trends in artificial intelligence publications in medicine versus cardiology.
A, Trends in the number of publications in PubMed returned by searching “artificial intelligence + medicine” as a keyword. B, Trends when searching for “artificial intelligence + cardiology.”
See this image and copyright information in PMC

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References

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    1. Fornwalt BK, Pfeifer JM. Promise and frustration: machine learning in cardiology. Circ Cardiovasc Imaging. 2021;14:e012838. doi: 10.1161/circimaging.121.012838 - DOI - PubMed
    1. Balch JA, Loftus TJ. Actionable artificial intelligence: overcoming barriers to adoption of prediction tools. Surgery. 2023;174:730–732. doi: 10.1016/j.surg.2023.03.019 - DOI - PubMed
    1. Butler L, Gunturkun F, Karabayir I, Akbilgic O. Logistic regression is also a black box. Machine learning can help. In: Shaban‐Nejad A, Michalowski M, Bianco S, eds AI for Disease Surveillance and Pandemic Intelligence: Intelligent Disease Detection in Action. Cham: Springer International Publishing; 2022:323–331. doi: 10.1007/978-3-030-93080-6_23 - DOI
    1. Kundu S. AI in medicine must be explainable. Nat Med. 2021;27:1328. doi: 10.1038/s41591-021-01461-z - DOI - PubMed

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