Comparison of machine learning and nomogram to predict 30-day in-hospital mortality in patients with acute myocardial infarction combined with cardiogenic shock: a retrospective study based on the eICU-CRD and MIMIC-IV databases
Abstract Background To evaluate the predictive utility of machine learning and nomogram in predicting in-hospital mortality in patients with acute myocardial infarction complicated by cardiogenic shock (AMI-CS), and to visualize the model results in order to analyze the impact of these predictors on...
I tiakina i:
| Ngā kaituhi matua: | , , , , |
|---|---|
| Hōputu: | Artigo |
| Reo: | Inglês |
| I whakaputaina: |
BMC
2025-03-01
|
| Rangatū: | BMC Cardiovascular Disorders |
| Ngā marau: | |
| Urunga tuihono: | https://doi.org/10.1186/s12872-025-04628-5 |
| Ngā Tūtohu: |
Kāore He Tūtohu, Me noho koe te mea tuatahi ki te tūtohu i tēnei pūkete!
|