Radiomics-based machine learning models in STEMI: a promising tool for the prediction of major adverse cardiac events

ES Durmaz, M Karabacak, BB Ozkara, OA Kargın… - European …, 2023 - Springer
Objective To evaluate the potential value of the machine learning (ML) models using
radiomic features of late gadolinium enhancement (LGE) and cine images on magnetic …
被引用次数：11 相关文章

Radiomics-based machine learning models in STEMI: a promising tool for the prediction of major adverse cardiac events.

ES Durmaz, M Karabacak, BB Ozkara… - European …, 2023 - search.ebscohost.com
Objective: To evaluate the potential value of the machine learning (ML) models using
radiomic features of late gadolinium enhancement (LGE) and cine images on magnetic …

Radiomics-based machine learning models in STEMI: a promising tool for the prediction of major adverse cardiac events

ES Durmaz, M Karabacak, BB Ozkara… - European …, 2023 - pubmed.ncbi.nlm.nih.gov
Objective To evaluate the potential value of the machine learning (ML) models using
radiomic features of late gadolinium enhancement (LGE) and cine images on magnetic …

Radiomics-based machine learning models in STEMI: a promising tool for the prediction of major adverse cardiac events

E DURMAZ, M Karabacak, B Ozkara… - EUROPEAN …, 2023 - avesis.istanbul.edu.tr
Objective To evaluate the potential value of the machine learning (ML) models using
radiomic features of late gadolinium enhancement (LGE) and cine images on magnetic …

Radiomics-based machine learning models in STEMI. A promising tool for the prediction of major adverse cardiac events

ES Durmaz, OA Kargın, I Adaletli… - European Radiology …, 2023 - inis.iaea.org
[en] To evaluate the potential value of the machine learning (ML) models using radiomic
features of late gadolinium enhancement (LGE) and cine images on magnetic resonance …

Radiomics-based machine learning models in STEMI: a promising tool for the prediction of major adverse cardiac events.

ES Durmaz, M Karabacak, BB Ozkara… - European …, 2023 - europepmc.org
Objective To evaluate the potential value of the machine learning (ML) models using
radiomic features of late gadolinium enhancement (LGE) and cine images on magnetic …