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Patient Admission

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Low vitamin D at ICU admission is associated with cancer, infections, acute respiratory insufficiency, and liver failure.

Nutrition (Burbank, Los Angeles County, Calif.) 30682545
OBJECTIVES: Vitamin D deficiency may be associated with comorbidities and poor prognosis. However, this association in patients in the intensive care unit (ICU) has not been fully elucidated. The aim of this study was to investigate whether the serum...
Acute Disease Adult Aged APACHE C-Reactive Protein Comorbidity Critical Illness Cross-Sectional Studies Female Hospital Mortality Humans Infections Intensive Care Units Liver Failure Male Middle Aged Neoplasms Organ Dysfunction Scores Patient Admission Prognosis Respiration, Artificial Respiratory Insufficiency Severity of Illness Index Time Factors Vitamin D Vitamin D Deficiency
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Optimal intensive care outcome prediction over time using machine learning.

PloS one 30427913
BACKGROUND: Prognostication is an essential tool for risk adjustment and decision making in the intensive care unit (ICU). Research into prognostication in ICU has so far been limited to data from admission or the first 24 hours. Most ICU admissions ...
Aged APACHE Clinical Decision-Making Critical Care Datasets as Topic Decision Support Systems, Clinical Feasibility Studies Female Hospital Mortality Humans Intensive Care Units Logistic Models Machine Learning Male Middle Aged Patient Admission Prognosis Retrospective Studies Risk Assessment ROC Curve Sepsis
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Predicting hospital admission at emergency department triage using machine learning.

PloS one 30028888
OBJECTIVE: To predict hospital admission at the time of ED triage using patient history in addition to information collected at triage.
Adult Emergency Service, Hospital Female Humans Machine Learning Male Middle Aged Models, Statistical Patient Admission Patient Discharge Triage
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A comparison of logistic regression models with alternative machine learning methods to predict the risk of in-hospital mortality in emergency medical admissions via external validation.

Health informatics journal 30488755
We compare the performance of logistic regression with several alternative machine learning methods to estimate the risk of death for patients following an emergency admission to hospital based on the patients' first blood test results and physiologi...
Emergency Service, Hospital Hospital Mortality Hospitalization Humans Logistic Models Machine Learning Patient Admission ROC Curve
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The Sydney Triage to Admission Risk Tool (START2) using machine learning techniques to support disposition decision-making.

Emergency medicine Australasia : EMA 30469164
OBJECTIVE: To further develop and refine an Emergency Department (ED) in-patient admission prediction model using machine learning techniques.
Adolescent Adult Aged Aged, 80 and over Area Under Curve Bayes Theorem Emergency Service, Hospital Female Forecasting Humans Logistic Models Machine Learning Male Middle Aged New South Wales Patient Admission Retrospective Studies ROC Curve Triage
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Predicting the risk of emergency admission with machine learning: Development and validation using linked electronic health records.

PLoS medicine 30458006
BACKGROUND: Emergency admissions are a major source of healthcare spending. We aimed to derive, validate, and compare conventional and machine learning models for prediction of the first emergency admission. Machine learning methods are capable of ca...
Adolescent Adult Age Factors Aged Aged, 80 and over Data Mining Electronic Health Records Emergency Service, Hospital England Female Health Services Needs and Demand Health Status Humans Machine Learning Male Middle Aged Needs Assessment Patient Admission Reproducibility of Results Risk Assessment Risk Factors Sex Factors Socioeconomic Factors Time Factors Young Adult
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Fuzzy logic and hospital admission due to respiratory diseases using estimated values by mathematical model.

Ciencia & saude coletiva 30892528
Hospitalizations due to respiratory diseases generate financial costs for the Health System in addition to social costs. Objective of this study was to develop and validate a fuzzy linguistic model for prediction of hospitalization due to respiratory...
Air Pollutants Air Pollution Brazil Environmental Exposure Fuzzy Logic Hospitalization Humans Models, Theoretical Particulate Matter Patient Admission Reproducibility of Results Respiratory Tract Diseases Sensitivity and Specificity
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Using machine-learning methods to support health-care professionals in making admission decisions.

The International journal of health planning and management 30957270
BACKGROUND: Large tertiary hospitals usually face long waiting lines; patients who want to receive hospitalization need to be screened in advance. The patient admission screening process involves a health-care professional ranking patients by analyzi...
Decision Support Systems, Clinical Humans Logistic Models Machine Learning Patient Admission
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Artificial intelligence and the clinical world: a view from the front line.

The Medical journal of Australia 30927469
Artificial Intelligence Australia Decision Support Techniques Emergency Service, Hospital General Practice Humans Patient Admission
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Supervised machine learning for the prediction of infection on admission to hospital: a prospective observational cohort study.

The Journal of antimicrobial chemotherapy 30590545
BACKGROUND: Infection diagnosis can be challenging, relying on clinical judgement and non-specific markers of infection. We evaluated a supervised machine learning (SML) algorithm for diagnosing bacterial infection using routinely available blood par...
Adult Aged Aged, 80 and over Algorithms Biomarkers Clinical Decision-Making Cohort Studies Decision Support Systems, Clinical Diagnostic Tests, Routine Disease Management Female Follow-Up Studies Hematologic Tests Humans Infections Male Middle Aged Patient Admission Prognosis ROC Curve Supervised Machine Learning Young Adult
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