Predicting functional results of percutaneous coronary intervention using machine learning modelling.

Fezzi S, Zhu Y, Bargary N, Ding D, Scarsini R, Lunardi M, Leone AM, Mammone C, Wagener M, McInerney A, Toth GG, Pesarini G, Connolly D, Trani C, Tu S, Burzotta F, Ribichini F, Simpkin AJ, Wijns W

Open source

DOI
10.1016/j.ijcard.2026.134183
Published
2026 Apr 15
Container
International journal of cardiology
Publisher
Not recorded
Open access
no

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BibTeX

@article{allodium:10.1016/j.ijcard.2026.134183,
  title = {Predicting functional results of percutaneous coronary intervention using machine learning modelling.},
  author = {Fezzi S and Zhu Y and Bargary N and Ding D and Scarsini R and Lunardi M and Leone AM and Mammone C and Wagener M and McInerney A and Toth GG and Pesarini G and Connolly D and Trani C and Tu S and Burzotta F and Ribichini F and Simpkin AJ and Wijns W},
  year = {2026},
  journal = {International journal of cardiology},
  doi = {10.1016/j.ijcard.2026.134183},
  url = {https://doi.org/10.1016/j.ijcard.2026.134183}
}

RIS

TY  - JOUR
TI  - Predicting functional results of percutaneous coronary intervention using machine learning modelling.
AU  - Fezzi S
AU  - Zhu Y
AU  - Bargary N
AU  - Ding D
AU  - Scarsini R
AU  - Lunardi M
AU  - Leone AM
AU  - Mammone C
AU  - Wagener M
AU  - McInerney A
AU  - Toth GG
AU  - Pesarini G
AU  - Connolly D
AU  - Trani C
AU  - Tu S
AU  - Burzotta F
AU  - Ribichini F
AU  - Simpkin AJ
AU  - Wijns W
PY  - 2026
JO  - International journal of cardiology
DO  - 10.1016/j.ijcard.2026.134183
UR  - https://doi.org/10.1016/j.ijcard.2026.134183
ER  - 

APA

S, F., Y, Z., N, B., D, D., R, S., M, L., AM, L., C, M., M, W., A, M., GG, T., G, P., D, C., C, T., S, T., F, B., F, R., AJ, S., & W, W. (2026). Predicting functional results of percutaneous coronary intervention using machine learning modelling.. International journal of cardiology. https://doi.org/10.1016/j.ijcard.2026.134183

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