AIMC Topic: Hospitalization
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Prediction and detection models for acute kidney injury in hospitalized older adults.
BMC medical informatics and decision making
Mar 29, 2016
BACKGROUND: Acute Kidney Injury (AKI) occurs in at least 5 % of hospitalized patients and can result in 40-70 % morbidity and mortality. Even following recovery, many subjects may experience progressive deterioration of renal function. The heterogene...
Development of two artificial neural network models to support the diagnosis of pulmonary tuberculosis in hospitalized patients in Rio de Janeiro, Brazil.
Medical & biological engineering & computing
Mar 25, 2016
Pulmonary tuberculosis (PTB) remains a worldwide public health problem. Diagnostic algorithms to identify the best combination of diagnostic tests for PTB in each setting are needed for resource optimization. We developed one artificial neural networ...
Automated identification and predictive tools to help identify high-risk heart failure patients: pilot evaluation.
Journal of the American Medical Informatics Association : JAMIA
Feb 17, 2016
OBJECTIVE: Develop and evaluate an automated identification and predictive risk report for hospitalized heart failure (HF) patients.
Prediction of In-hospital Mortality in Emergency Department Patients With Sepsis: A Local Big Data-Driven, Machine Learning Approach.
Academic emergency medicine : official journal of the Society for Academic Emergency Medicine
Feb 13, 2016
OBJECTIVES: Predictive analytics in emergency care has mostly been limited to the use of clinical decision rules (CDRs) in the form of simple heuristics and scoring systems. In the development of CDRs, limitations in analytic methods and concerns wit...
Outcome Prediction in Clinical Treatment Processes.
Journal of medical systems
Oct 29, 2015
Clinical outcome prediction, as strong implications for health service delivery of clinical treatment processes (CTPs), is important for both patients and healthcare providers. Prior studies typically use a priori knowledge, such as demographics or p...
A novel method of adverse event detection can accurately identify venous thromboembolisms (VTEs) from narrative electronic health record data.
Journal of the American Medical Informatics Association : JAMIA
Oct 20, 2014
BACKGROUND: Venous thromboembolisms (VTEs), which include deep vein thrombosis (DVT) and pulmonary embolism (PE), are associated with significant mortality, morbidity, and cost in hospitalized patients. To evaluate the success of preventive measures,...
Prediction of hospitalization due to heart diseases by supervised learning methods.
International journal of medical informatics
Oct 16, 2014
BACKGROUND: In 2008, the United States spent $2.2 trillion for healthcare, which was 15.5% of its GDP. 31% of this expenditure is attributed to hospital care. Evidently, even modest reductions in hospital care costs matter. A 2009 study showed that n...
Artificial intelligence-assisted quality control circles led by clinical pharmacists to improve the rational use of parenteral proton pump inhibitors among hospitalised patients.
Scientific reports
Aug 26, 2025
Proton pump inhibitors (PPIs) are a class of drugs that inhibit gastric acid secretion and are commonly overused in clinical practice. We developed a quality control circle (QCC) assisted by artificial intelligence (AI) and led by clinical pharmacist...
Young infants with bronchiolitis at low risk of respiratory deterioration in an urban, academic emergency department: prospective cohort study protocol.
BMJ open
Aug 26, 2025
INTRODUCTION: Bronchiolitis, a viral lower respiratory tract infection, is the leading cause of hospitalisation for infants, with healthcare utilisation highest among young infants (aged ≤90 days). Clinical models to predict respiratory deterioration...
Pilot Application of a Large Language Model to Identify Hospitalisation from Unstructured Electronic Health Records in Residential Aged Care Facilities.
Studies in health technology and informatics
Aug 7, 2025
Older people in residential aged care facilities (RACFs) visit hospitals and utilise healthcare services more often than others in the community. Trends in hospitalization rates are essential for designing targeted aged care interventions to reduce p...
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