AIMC Topic: Intensive Care Units

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Continuous and automatic mortality risk prediction using vital signs in the intensive care unit: a hybrid neural network approach.

Scientific reports Dec 4, 2020
Mortality risk prediction can greatly improve the utilization of resources in intensive care units (ICUs). Existing schemes in ICUs today require laborious manual input of many complex parameters. In this work, we present a scheme that uses variation...
Hospital Mortality Patient Acuity Vital Signs Aged, 80 and over Young Adult Adult Male Algorithms Middle Aged Intensive Care Units Risk Assessment Female Adolescent Aged Humans Neural Networks, Computer
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Assessment of Machine Learning to Estimate the Individual Treatment Effect of Corticosteroids in Septic Shock.

JAMA network open Dec 1, 2020
IMPORTANCE: The survival benefit of corticosteroids in septic shock remains uncertain.
Clinical Decision-Making Female Aged Male Machine Learning Prognosis Intensive Care Units Hydrocortisone Critical Care Risk Adjustment Organ Dysfunction Scores Glucocorticoids Shock, Septic Randomized Controlled Trials as Topic Humans Fludrocortisone
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Using machine learning tools to predict outcomes for emergency department intensive care unit patients.

Scientific reports Dec 1, 2020
The number of critically ill patients has increased globally along with the rise in emergency visits. Mortality prediction for critical patients is vital for emergency care, which affects the distribution of emergency resources. Traditional scoring s...
Humans Machine Learning Intensive Care Units Female Treatment Outcome Area Under Curve Emergency Service, Hospital Models, Biological Aged Male Middle Aged ROC Curve
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A neural network for prediction of risk of nosocomial infection at intensive care units: a didactic preliminary model.

Einstein (Sao Paulo, Brazil) Nov 20, 2020
OBJECTIVE: To propose a preliminary artificial intelligence model, based on artificial neural networks, for predicting the risk of nosocomial infection at intensive care units.
Cross Infection Algorithms Humans Intensive Care Units Neural Networks, Computer Risk Assessment Artificial Intelligence APACHE
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Intelligent checklists improve checklist compliance in the intensive care unit: a prospective before-and-after mixed-method study.

British journal of anaesthesia Nov 17, 2020
BACKGROUND: We examined whether a context and process-sensitive 'intelligent' checklist increases compliance with best practice compared with a paper checklist during intensive care ward rounds.
Quality Indicators, Health Care Practice Guidelines as Topic Checklist Practice Patterns, Physicians' Attitude to Computers Patient Safety Teaching Rounds Prospective Studies Intensive Care Units Paper Length of Stay Benchmarking Decision Support Systems, Clinical Critical Care Guideline Adherence Humans Quality Improvement Health Status Artificial Intelligence
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Prognostic Assessment of COVID-19 in the Intensive Care Unit by Machine Learning Methods: Model Development and Validation.

Journal of medical Internet research Nov 11, 2020
BACKGROUND: Patients with COVID-19 in the intensive care unit (ICU) have a high mortality rate, and methods to assess patients' prognosis early and administer precise treatment are of great significance.
Retrospective Studies Intensive Care Units Female Reproducibility of Results Risk Factors Male Humans Machine Learning COVID-19 Algorithms Prognosis
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SSP: Early prediction of sepsis using fully connected LSTM-CNN model.

Computers in biology and medicine Nov 10, 2020
BACKGROUND: Sepsis is a life-threatening condition that occurs due to the body's reaction to infections, and it is a leading cause of morbidity and mortality in hospitals. Early prediction of sepsis onset facilitates early interventions that promote ...
Neural Networks, Computer Vital Signs Machine Learning Humans Intensive Care Units Sepsis
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Artificial Intelligence in the Intensive Care Unit.

Seminars in respiratory and critical care medicine Nov 5, 2020
The diffusion of electronic health records collecting large amount of clinical, monitoring, and laboratory data produced by intensive care units (ICUs) is the natural terrain for the application of artificial intelligence (AI). AI has a broad definit...
Humans Electronic Health Records Sepsis Artificial Intelligence Machine Learning Intensive Care Units
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Left ventricular systolic dysfunction identification using artificial intelligence-augmented electrocardiogram in cardiac intensive care unit patients.

International journal of cardiology Nov 2, 2020
BACKGROUND: An artificial intelligence-augmented electrocardiogram (AI-ECG) can identify left ventricular systolic dysfunction (LVSD). We examined the accuracy of AI ECG for identification of LVSD (defined as LVEF ≤40% by transthoracic echocardiogram...
Electrocardiography Ventricular Dysfunction, Left Intensive Care Units Female Aged Humans Aged, 80 and over Artificial Intelligence Male Echocardiography Middle Aged
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A deep learning approach for sepsis monitoring via severity score estimation.

Computer methods and programs in biomedicine Oct 28, 2020
BACKGROUND AND OBJECTIVE: Sepsis occurs in response to an infection in the body and can progress to a fatal stage. Detection and monitoring of sepsis require multi-step analysis, which is time-consuming, costly and requires medically trained personne...
ROC Curve Organ Dysfunction Scores Humans Prognosis Retrospective Studies Intensive Care Units Deep Learning Sepsis
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