Cargando…
Predicting 90-Day Prognosis in Ischemic Stroke Patients Post Thrombolysis Using Machine Learning
(1) Objective: This study aimed to construct a machine learning model for predicting the prognosis of ischemic stroke patients who underwent thrombolysis, assessed through the modified Rankin Scale (mRS) score 90 days after discharge. (2) Methods: Data were sourced from Qatar’s stroke registry cover...
Autores principales: | Abujaber, Ahmad A., Albalkhi, Ibrahem, Imam, Yahia, Nashwan, Abdulqadir J., Yaseen, Said, Akhtar, Naveed, Alkhawaldeh, Ibraheem M. |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10672468/ https://www.ncbi.nlm.nih.gov/pubmed/38003870 http://dx.doi.org/10.3390/jpm13111555 |
Ejemplares similares
-
Harnessing Large Language Models in Nursing Care Planning: Opportunities, Challenges, and Ethical Considerations
por: Nashwan, Abdulqadir J, et al.
Publicado: (2023) -
Nursing in the Artificial Intelligence (AI) Era: Optimizing Staffing for Tomorrow
por: Nashwan, Abdulqadir J, et al.
Publicado: (2023) -
Harnessing the Power of Large Language Models (LLMs) for Electronic Health Records (EHRs) Optimization
por: Nashwan, Abdulqadir J, et al.
Publicado: (2023) -
Late small bowel perforation from a migrated double plastic biliary stent: A case report and a review of literature of 85 cases from 2000 to 2022
por: Alkhawaldeh, Ibraheem M., et al.
Publicado: (2023) -
Neutrophil-Related Ratios Predict the 90-Day Outcome in Acute Ischemic Stroke Patients After Intravenous Thrombolysis
por: Gao, Beibei, et al.
Publicado: (2021)