Analysis of the quality of an artificial intelligence mobile application for electrocardiogram interpretation

Authors

  • Rodrigo Chavez-Ecos CHANGE Research Working Group, Facultad de Ciencias de la Salud, Carrera de Medicina Humana, Universidad Científica del Sur, Lima, Perú. https://orcid.org/0009-0009-5285-0393
  • Kiara Camacho-Caballero CHANGE Research Working Group, Facultad de Ciencias de la Salud, Carrera de Medicina Humana, Universidad Científica del Sur, Lima, Perú. https://orcid.org/0000-0002-3609-2424
  • Marcelo S. Chavez-Ecos CHANGE Research Working Group, Facultad de Ciencias de la Salud, Carrera de Medicina Humana, Universidad Científica del Sur, Lima, Perú. https://orcid.org/0009-0002-9833-7543
  • Miguel A. Chavez-Gutarra Facultad de Medicina Humana, Universidad Nacional San Luis Gonzaga, Ica, Perú. https://orcid.org/0009-0000-7022-4315
  • Oscar Aguirre-Zurita Instituto Nacional Cardiovascular «Carlos Alberto Peschiera Carrillo», Departamento de Cardiología, INCOR, Lima, Perú. https://orcid.org/0000-0003-3517-0395
  • Fabian A. Chavez-Ecos CHANGE Research Working Group, Facultad de Ciencias de la Salud, Carrera de Medicina Humana, Universidad Científica del Sur, Lima, Perú; Facultad de Medicina Humana, Universidad Nacional San Luis Gonzaga, Ica, Perú.

DOI:

https://doi.org/10.47487/apcyccv.v5i2.363

Keywords:

Artificial Intelligence, Electrocardiography

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References

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Steubl LS, Reimann J, Simon L, Terhorst Y, Stach M, Baumeister H, et al. A systematic quality rating of available mobile health apps for borderline personality disorder. Borderline Personal Disord Emot Dysregul. 2022;9(1):1-10. doi: 10.1186/s40479-022-00186-w.

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Published

2024-04-15

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Letters to the editor