AIMC Topic: Intensive Care Units

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Dynamic Mortality Risk Predictions for Children in ICUs: Development and Validation of Machine Learning Models.

Pediatric critical care medicine : a journal of the Society of Critical Care Medicine and the World Federation of Pediatric Intensive and Critical Care Societies May 5, 2022
OBJECTIVES: Assess a machine learning method of serially updated mortality risk.
Humans Machine Learning Child Hospital Mortality ROC Curve Retrospective Studies Intensive Care Units
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POTTER-ICU: An artificial intelligence smartphone-accessible tool to predict the need for intensive care after emergency surgery.

Surgery Apr 28, 2022
BACKGROUND: Delays in admitting high-risk emergency surgery patients to the intensive care unit result in worse outcomes and increased health care costs. We aimed to use interpretable artificial intelligence technology to create a preoperative predic...
Critical Care Postoperative Complications Smartphone Intensive Care Units Female Male Humans Middle Aged Adult Artificial Intelligence Retrospective Studies
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Learning to predict in-hospital mortality risk in the intensive care unit with attention-based temporal convolution network.

BMC anesthesiology Apr 23, 2022
BACKGROUND: Dynamic prediction of patient mortality risk in the ICU with time series data is limited due to high dimensionality, uncertainty in sampling intervals, and other issues. A new deep learning method, temporal convolution network (TCN), make...
Artificial Intelligence Intensive Care Units Hospital Mortality ROC Curve Hospitalization Humans
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Implementation of a machine learning application in preoperative risk assessment for hip repair surgery.

BMC anesthesiology Apr 23, 2022
BACKGROUND: This study aims to develop a machine learning-based application in a real-world medical domain to assist anesthesiologists in assessing the risk of complications in patients after a hip surgery.
Retrospective Studies Intensive Care Units Humans Machine Learning Hospital Mortality ROC Curve Area Under Curve Adult Risk Assessment
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Deep learning of chest X-rays can predict mechanical ventilation outcome in ICU-admitted COVID-19 patients.

Scientific reports Apr 13, 2022
The COVID-19 pandemic repeatedly overwhelms healthcare systems capacity and forced the development and implementation of triage guidelines in ICU for scarce resources (e.g. mechanical ventilation). These guidelines were often based on known risk fact...
Respiration, Artificial Deep Learning X-Rays COVID-19 Intensive Care Units Humans Pandemics
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Big Data and Artificial Intelligence in Intensive Care Unit: From "Bla, Bla, Bla" to the Incredible Five V's.

Neurocritical care Apr 12, 2022
Intensive Care Units Big Data Humans Artificial Intelligence
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A Machine Learning Model for Early Prediction and Detection of Sepsis in Intensive Care Unit Patients.

Journal of healthcare engineering Mar 26, 2022
In today's scenario, sepsis is impacting millions of patients in the intensive care unit due to the fact that the mortality rate is increased exponentially and has become a major challenge in the field of healthcare. Such peoples require determinant ...
Bayes Theorem Intensive Care Units Humans Sepsis Machine Learning Critical Care
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Early identification of ICU patients at risk of complications: Regularization based on robustness and stability of explanations.

Artificial intelligence in medicine Mar 22, 2022
The aim of this study is to build machine learning models to predict severe complications using administrative and clinical elements that are collected immediately after patient admission to the intensive care unit (ICU). Risk models are of increasin...
Critical Care Humans Intensive Care Units Machine Learning Risk Assessment Algorithms Retrospective Studies
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Artificial Intelligence in Infection Management in the ICU.

Critical care (London, England) Mar 22, 2022
This article is one of ten reviews selected from the Annual Update in Intensive Care and Emergency Medicine 2022. Other selected articles can be found online at https://www.biomedcentral.com/collections/annualupdate2022 . Further information about th...
Humans Intensive Care Units Critical Care Emergency Medicine Artificial Intelligence
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A hybrid Neural Network-SEIR model for forecasting intensive care occupancy in Switzerland during COVID-19 epidemics.

PloS one Mar 3, 2022
Anticipating intensive care unit (ICU) occupancy is critical in supporting decision makers to impose (or relax) measures that mitigate COVID-19 transmission. Mechanistic approaches such as Susceptible-Infected-Recovered (SIR) models have traditionall...
Humans Intensive Care Units Neural Networks, Computer SARS-CoV-2 Bed Occupancy COVID-19 Switzerland Forecasting Critical Care
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