AIMC Topic: Patient Admission

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Prediction of admission in pediatric emergency department with deep neural networks and triage textual data.

Neural networks : the official journal of the International Neural Network Society Mar 18, 2020
Emergency department (ED) overcrowding is a global condition that severely worsens attention to patients, increases clinical risks and affects hospital cost management. A correct and early prediction of ED's admission is of high value and a motivatio...
Neural Networks, Computer Forecasting Databases, Factual Female Hospitalization Humans Child Triage Emergency Service, Hospital Pediatrics Patient Admission Male Infant Deep Learning Cohort Studies Child, Preschool
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Comparison of Prediction Model Performance Updating Protocols: Using a Data-Driven Testing Procedure to Guide Updating.

AMIA ... Annual Symposium proceedings. AMIA Symposium Mar 4, 2020
In evolving clinical environments, the accuracy of prediction models deteriorates over time. Guidance on the design of model updating policies is limited, and there is limited exploration of the impact of different policies on future model performanc...
Humans Neural Networks, Computer Hospital Mortality Logistic Models United States Models, Statistical Health Facilities United States Department of Veterans Affairs Patient Admission
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Combining patient visual timelines with deep learning to predict mortality.

PloS one Jul 31, 2019
BACKGROUND: Deep learning algorithms have achieved human-equivalent performance in image recognition. However, the majority of clinical data within electronic health records is inherently in a non-image format. Therefore, creating visual representati...
Neural Networks, Computer Machine Learning Retrospective Studies Intensive Care Units Electronic Health Records Humans Deep Learning Hospital Mortality ROC Curve Patient Admission Vital Signs Female Hospitalization Male Middle Aged
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Modelling outcomes after paediatric brain injury with admission laboratory values: a machine-learning approach.

Pediatric research Jul 26, 2019
BACKGROUND: Severe traumatic brain injury (TBI) is a leading cause of mortality in children, but the accurate prediction of outcomes at the point of admission remains very challenging. Admission laboratory results are a promising potential source of ...
Treatment Outcome Brain Injuries Patient Admission Humans Machine Learning Female Male Child
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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 Apr 7, 2019
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...
Humans Machine Learning Decision Support Systems, Clinical Logistic Models Patient Admission
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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 Nov 29, 2018
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...
Humans Machine Learning Hospitalization Hospital Mortality ROC Curve Logistic Models Emergency Service, Hospital Patient Admission
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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 Nov 23, 2018
OBJECTIVE: To further develop and refine an Emergency Department (ED) in-patient admission prediction model using machine learning techniques.
Humans Machine Learning ROC Curve Logistic Models Triage Area Under Curve Emergency Service, Hospital Bayes Theorem Patient Admission New South Wales Aged, 80 and over Adult Male Middle Aged Adolescent Forecasting Retrospective Studies Female Aged
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Predicting the risk of emergency admission with machine learning: Development and validation using linked electronic health records.

PLoS medicine Nov 20, 2018
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...
Sex Factors Health Services Needs and Demand Patient Admission Needs Assessment Middle Aged Risk Assessment England Adolescent Time Factors Socioeconomic Factors Health Status Age Factors Emergency Service, Hospital Data Mining Aged Aged, 80 and over Young Adult Adult Male Electronic Health Records Female Reproducibility of Results Risk Factors Humans Machine Learning
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Optimal intensive care outcome prediction over time using machine learning.

PloS one Nov 14, 2018
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 ...
Feasibility Studies Humans Critical Care Datasets as Topic Machine Learning APACHE Patient Admission Hospital Mortality Aged ROC Curve Male Decision Support Systems, Clinical Prognosis Middle Aged Logistic Models Retrospective Studies Risk Assessment Intensive Care Units Sepsis Clinical Decision-Making Female
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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.) Oct 24, 2018
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...
Liver Failure Organ Dysfunction Scores Patient Admission Acute Disease Respiratory Insufficiency APACHE Middle Aged Infections Neoplasms Respiration, Artificial Comorbidity Severity of Illness Index Time Factors Hospital Mortality Female Vitamin D Humans Aged Prognosis Vitamin D Deficiency Adult Critical Illness C-Reactive Protein Cross-Sectional Studies Intensive Care Units Male
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