AIMC Topic: Intensive Care Units

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Genetic prediction of ICU hospitalization and mortality in COVID-19 patients using artificial neural networks.

Journal of cellular and molecular medicine Jan 22, 2022
There is an unmet need of models for early prediction of morbidity and mortality of Coronavirus disease-19 (COVID-19). We aimed to a) identify complement-related genetic variants associated with the clinical outcomes of ICU hospitalization and death,...
Female Hospitalization Male Neural Networks, Computer COVID-19 Intensive Care Units Morbidity Greece Thrombomodulin Middle Aged Polymorphism, Single Nucleotide Models, Genetic Humans Complement Factor H Complement Activation Complement System Proteins
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Improving the In-Hospital Mortality Prediction of Diabetes ICU Patients Using a Process Mining/Deep Learning Architecture.

IEEE journal of biomedical and health informatics Jan 17, 2022
Diabetes intensive care unit (ICU) patients are at increased risk of complications leading to in-hospital mortality. Assessing the likelihood of death is a challenging and time-consuming task due to a large number of influencing factors. Healthcare p...
Hospital Mortality Diabetes Mellitus Humans Critical Care Intensive Care Units Deep Learning
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Ethical Considerations Related to Using Machine Learning-Based Prediction of Mortality in the Pediatric Intensive Care Unit.

The Journal of pediatrics Jan 14, 2022
Child Humans Intensive Care Units, Pediatric Machine Learning Intensive Care Units
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Unstructured clinical notes within the 24 hours since admission predict short, mid & long-term mortality in adult ICU patients.

PloS one Jan 6, 2022
Mortality prediction for intensive care unit (ICU) patients is crucial for improving outcomes and efficient utilization of resources. Accessibility of electronic health records (EHR) has enabled data-driven predictive modeling using machine learning....
ROC Curve Humans Logistic Models Electronic Health Records Machine Learning Area Under Curve Length of Stay Databases, Factual Hospital Mortality Intensive Care Units
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SWIFT: A deep learning approach to prediction of hypoxemic events in critically-Ill patients using SpO2 waveform prediction.

PLoS computational biology Dec 21, 2021
Hypoxemia is a significant driver of mortality and poor clinical outcomes in conditions such as brain injury and cardiac arrest in critically ill patients, including COVID-19 patients. Given the host of negative clinical outcomes attributed to hypoxe...
Deep Learning Hypoxia Oxygen Saturation Critical Illness Humans Intensive Care Units Pandemics SARS-CoV-2 COVID-19
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Needs Assessment Survey Identifying Research Processes Which may be Improved by Automation or Artificial Intelligence: ICU Community Modeling and Artificial Intelligence to Improve Efficiency (ICU-Comma).

Journal of intensive care medicine Dec 13, 2021
BACKGROUND: Critical care research in Canada is conducted primarily in academically-affiliated intensive care units with established research infrastructure, including research coordinators (RCs). Recently, efforts have been made to engage community ...
Automation Needs Assessment Cross-Sectional Studies Canada Humans Artificial Intelligence Intensive Care Units
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Real-Time Arrhythmia Detection Using Hybrid Convolutional Neural Networks.

Journal of the American Heart Association Dec 2, 2021
Background Accurate detection of arrhythmic events in the intensive care units (ICU) is of paramount significance in providing timely care. However, traditional ICU monitors generate a high rate of false alarms causing alarm fatigue. In this work, we...
Neural Networks, Computer Algorithms Intensive Care Units Reproducibility of Results Arrhythmias, Cardiac Humans
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Application of Deep Learning Technology in Predicting the Risk of Inpatient Death in Intensive Care Unit.

Journal of healthcare engineering Dec 1, 2021
The Intensive Care Unit (ICU) is an important unit for the rescue of critically ill patients in hospitals, and patient mortality is an important indicator to measure the level of ICU treatment. Currently, a variety of clinical scoring systems are use...
Inpatients Intensive Care Units Risk Factors Deep Learning Humans Artificial Intelligence Technology
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The new SUMPOT to predict postoperative complications using an Artificial Neural Network.

Scientific reports Nov 22, 2021
An accurate assessment of preoperative risk may improve use of hospital resources and reduce morbidity and mortality in high-risk surgical patients. This study aims at implementing an automated surgical risk calculator based on Artificial Neural Netw...
Cohort Studies ROC Curve Predictive Value of Tests Area Under Curve Elective Surgical Procedures Humans Emergency Treatment Neural Networks, Computer Middle Aged Risk Assessment Postoperative Complications Hospitalization Intensive Care Units Male Female Machine Learning Risk Factors Prognosis Retrospective Studies
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Influence of Critical Care Transport Ventilator Management on Intensive Care Unit Care.

Air medical journal Nov 20, 2021
OBJECTIVE: High tidal volume ventilation is associated with ventilator-induced lung injury. Early introduction of lung protective ventilation improves patient outcomes. This study describes ventilator management during critical care transport and the...
Tidal Volume Critical Care Ventilators, Mechanical Adult Humans Respiration, Artificial Intensive Care Units Respiratory Distress Syndrome
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