“Diagnostic Performance of Artificial Intelligence in Evaluating Tricuspid Regurgitation: A Systematic Review and Meta‐Analysis”

Pooya Eini, Homa Serpoush, Mohammad Rezayee, Milan Kassulke

Open source

DOI: 10.1002/clc.70366
Published: 2026-06
Container: Clinical Cardiology
Publisher: Wiley
Open access: unknown

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Cite this work

BibTeX

@article{allodium:10.1002/clc.70366,
  title = {“Diagnostic Performance of Artificial Intelligence in Evaluating Tricuspid Regurgitation: A Systematic Review and Meta‐Analysis”},
  author = {Pooya Eini and Homa Serpoush and Mohammad Rezayee and Milan Kassulke},
  year = {2026},
  journal = {Clinical Cardiology},
  doi = {10.1002/clc.70366},
  url = {https://doi.org/10.1002/clc.70366}
}

RIS

TY  - JOUR
TI  - “Diagnostic Performance of Artificial Intelligence in Evaluating Tricuspid Regurgitation: A Systematic Review and Meta‐Analysis”
AU  - Pooya Eini
AU  - Homa Serpoush
AU  - Mohammad Rezayee
AU  - Milan Kassulke
PY  - 2026
JO  - Clinical Cardiology
DO  - 10.1002/clc.70366
UR  - https://doi.org/10.1002/clc.70366
ER  -

APA

Eini, P., Serpoush, H., Rezayee, M., & Kassulke, M. (2026). “Diagnostic Performance of Artificial Intelligence in Evaluating Tricuspid Regurgitation: A Systematic Review and Meta‐Analysis”. Clinical Cardiology. https://doi.org/10.1002/clc.70366

Source records

crossref · retrieved 2026-09-24T21:33:36.871Z