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All Outputs (2)

Application of machine learning in predicting frailty syndrome in patients with heart failure (2024)
Journal Article
Szczepanowski, R., Uchmanowicz, I., Pasieczna-Dixit, A. H., Sobecki, J., Katarzyniak, R., Kołaczek, G., Lorkiewicz, W., Kędras, M., Dixit, A., Biegus, J., Wleklik, M., Gobbens, R. J., Hill, L., Jaarsma, T., Hussain, A., Barbagallo, M., Veronese, N., Morabito, F. C., & Kahsin, A. (2024). Application of machine learning in predicting frailty syndrome in patients with heart failure. Advances in Clinical and Experimental Medicine, 33(3), 309-315. https://doi.org/10.17219/acem/184040

Prevention and diagnosis of frailty syndrome (FS) in patients with heart failure (HF) require innovative systems to help medical personnel tailor and optimize their treatment and care. Traditional methods of diagnosing FS in patients could be more sa... Read More about Application of machine learning in predicting frailty syndrome in patients with heart failure.

Rationing of nursing care in Internal Medicine Departments—a cross-sectional study (2023)
Journal Article
Jędrzejczyk, M., Guzak, B., Czapla, M., Ross, C., Vellone, E., Juzwiszyn, J., Chudiak, A., Sadowski, M., & Uchmanowicz, I. (2023). Rationing of nursing care in Internal Medicine Departments—a cross-sectional study. BMC Nursing, 22(1), Article 455. https://doi.org/10.1186/s12912-023-01617-x

Background: Implicit rationing of nursing care refers to a situation in which necessary nursing care is not performed to meet all of the patients’ needs. Purpose: To examine the factors influencing the rationing of nursing care, nurses’ assessment of... Read More about Rationing of nursing care in Internal Medicine Departments—a cross-sectional study.