Article

Risk Score Models for Unplanned Urinary Tract Infection Hospitalization

2023-08-09

Abstract excerpt

Annually, urinary tract infections (UTIs) affect over a hundred million people worldwide. Early detection of high-risk individuals can help prevent hospitalization for UTIs, which imposes significant economic and social burden on patients and caregivers. We present two methods to generate risk score models for unplanned UTI hospitalization. We utilize a sample of patients from the insurance claims data provided by...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work: 89610c65-5340-576e-a7c0-3cb099ca5584
DOI: 10.1101/2023.08.06.23293723

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest

Risk Score Models for Unplanned Urinary Tract Infection HospitalizationDOI 10.1101/2023.08.06.23293723Read

Machine Learning for Urinary Tract Infection Prediction in Emergency Departments: An Explainable ApproachSemantic proximity Read

Interpretable Machine Learning-based Decision Support for Prediction of Antibiotic Resistance for Complicated Urinary Tract InfectionsSemantic proximity Read

Explainable machine learning to identify patients at risk of developing hospital acquired infectionsSemantic proximity Read

Risk Factors for Urinary Tract Infection (UTI) Among Home Health Care Patients: Analysis Using Routinely Collected Clinical DataSemantic proximity Read

Prediction of postoperative infections by strategic data imputation and explainable machine learningSemantic proximity Read

Construction of a Logistic-regression risk-based prediction model for hospital infection in obstetric inpatientsSemantic proximity Read

Reassessing the management of uncomplicated urinary tract infection: A retrospective analysis using machine learning causal inferenceSemantic proximity Read

HIV risk score and prediction model in the United States: A Scoping Review ProtocolSemantic proximity Read

Development and validation of interpretable Bayes machine learning model for risk adjustment of general outcome indicators: An example from UrologySemantic proximity Read

Design and applicability of clinical prediction models for serious infection in children with fever: a scoping review using causal directed acyclic graphsSemantic proximity Read

Evaluating the Bias, type I error and statistical power of the prior Knowledge-Guided integrated likelihood estimation (PIE) for bias reduction in EHR based association studies.Semantic proximity Read

Comparison of CRB/CRB-65, qSOFA, and SIRS for Risk Prediction in Patients with Urinary Tract InfectionSemantic proximity Read