Cargando…
Prediction Framework on Early Urine Infection in IoT–Fog Environment Using XGBoost Ensemble Model
Urine infections are one of the most prevalent concerns for the healthcare industry that may impair the functioning of the kidney and other renal organs. As a result, early diagnosis and treatment of such infections are essential to avert any future complications. Conspicuously, in the current work,...
| Autores principales: | , |
|---|---|
| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Springer US
2023
|
| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10123571/ https://www.ncbi.nlm.nih.gov/pubmed/37360131 http://dx.doi.org/10.1007/s11277-023-10466-5 |