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Editorial
. 2023 Jun;16(6):745-748.
doi: 10.1016/j.jcmg.2023.01.019. Epub 2023 Mar 23.

Refining Echocardiographic Surveillance of Aortic Stenosis Using Machine Learning: Toward Personalized and Sustainable Follow-Up Schemes

Attila Kovács  1 , Márton Tokodi  2
Affiliations
Free article
Editorial

Refining Echocardiographic Surveillance of Aortic Stenosis Using Machine Learning: Toward Personalized and Sustainable Follow-Up Schemes

Attila Kovács et al. JACC Cardiovasc Imaging. 2023 Jun.
Free article
No abstract available

Keywords: aortic stenosis; echocardiography; follow-up; machine learning; personalized medicine.

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Conflict of interest statement

Funding Support and Author Disclosures Project number RRF-2.3.1-21-2022-00004 (MILAB) has been implemented with support from the European Union. Dr Kovács has received grant support from the National Research, Development, and Innovation Office (NKFIH) of Hungary (FK 142573); serves as the Chief Medical Officer of Argus Cognitive, Inc; and has received personal fees from Argus Cognitive, Inc outside of the submitted paper. Dr Tokodi is a former employee of Argus Cognitive, Inc; and has received financial compensation for his work from Argus Cognitive, outside of the submitted paper.

Comment on

  • Machine Learning to Optimize the Echocardiographic Follow-Up of Aortic Stenosis.
    Sánchez-Puente A, Dorado-Díaz PI, Sampedro-Gómez J, Bermejo J, Martinez-Legazpi P, Fernández-Avilés F, Sánchez-González J, Pérez Del Villar C, Vicente-Palacios V, Sanchez PL. Sánchez-Puente A, et al. JACC Cardiovasc Imaging. 2023 Jun;16(6):733-744. doi: 10.1016/j.jcmg.2022.12.008. Epub 2023 Feb 8. JACC Cardiovasc Imaging. 2023. PMID: 36881417

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