Diabetic kidney disease phenotypes and the risk of cardiovascular events: The Silesia Diabetes-Heart Project.
- Published in:
- Cardiovascular Diabetology, 2025, v. 24, n. 1, p. 1, doi. 10.1186/s12933-025-02852-z
- By:
- Publication type:
- Article
Works by Wójcik, Wiktoria
Results: 5
1
2
Machine Learning Identifies Metabolic Dysfunction–Associated Steatotic Liver Disease in Patients With Diabetes Mellitus.
- Published in:
- Journal of Clinical Endocrinology & Metabolism, 2024, v. 109, n. 8, p. 2029, doi. 10.1210/clinem/dgae060
- By:
- Publication type:
- Article
3
MksB is a novel mycobacterial condensin that orchestrates spatiotemporal positioning of replication machinery.
- Published in:
- Scientific Reports, 2024, v. 14, n. 1, p. 1, doi. 10.1038/s41598-024-70054-w
- By:
- Publication type:
- Article
4
Predicting major adverse cardiac events in diabetes and chronic kidney disease: a machine learning study from the Silesia Diabetes-Heart Project.
- Published in:
- Cardiovascular Diabetology, 2025, v. 24, n. 1, p. 1, doi. 10.1186/s12933-025-02615-w
- By:
- Publication type:
- Article
5
Metabolically "extremely unhealthy" obese and non-obese people with diabetes and the risk of cardiovascular adverse events: the Silesia Diabetes - Heart Project.
- Published in:
- Cardiovascular Diabetology, 2024, v. 23, n. 1, p. 1, doi. 10.1186/s12933-024-02420-x
- By:
- Publication type:
- Article