Machine learning for hospital readmission prediction in pediatric population
NC da Silva, MK Albertini, AR Backes… - Computer Methods and …, 2024 - Elsevier
Background and objective Pediatric readmissions are a burden on patients, families, and the
healthcare system. In order to identify patients at higher readmission risk, more accurate …
healthcare system. In order to identify patients at higher readmission risk, more accurate …
Machine learning for hospital readmission prediction in pediatric population.
NCD Silva, MK Albertini, AR Backes… - Computer Methods and …, 2023 - europepmc.org
Methods Retrospective cohort study was carried out with 9,080 patients under 18 years old
admitted to a tertiary university hospital. Demographic, clinical, and biochemical data were …
admitted to a tertiary university hospital. Demographic, clinical, and biochemical data were …
Machine learning for hospital readmission prediction in pediatric population
NC da Silva, MK Albertini, AR Backes… - … and programs in … - pubmed.ncbi.nlm.nih.gov
Background and objective Pediatric readmissions are a burden on patients, families, and the
healthcare system. In order to identify patients at higher readmission risk, more accurate …
healthcare system. In order to identify patients at higher readmission risk, more accurate …
Machine learning for hospital readmission prediction in pediatric population
NC Silva, MK Albertini, AR Backes, GG Pena - 2024 - dl.acm.org
Background and objective Pediatric readmissions are a burden on patients, families, and the
healthcare system. In order to identify patients at higher readmission risk, more accurate …
healthcare system. In order to identify patients at higher readmission risk, more accurate …