AIMC Topic: Critical Care

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DeepSOFA: A Continuous Acuity Score for Critically Ill Patients using Clinically Interpretable Deep Learning.

Scientific reports Feb 12, 2019
Traditional methods for assessing illness severity and predicting in-hospital mortality among critically ill patients require time-consuming, error-prone calculations using static variable thresholds. These methods do not capitalize on the emerging a...
Young Adult Adult Male Middle Aged Severity of Illness Index Retrospective Studies Critical Illness Intensive Care Units Female Aged Decision Making Area Under Curve Humans Probability Databases, Factual Critical Care Organ Dysfunction Scores Deep Learning Length of Stay Adolescent Hospital Mortality Longitudinal Studies
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Potential EEG biomarkers of sedation doses in intensive care patients unveiled by using a machine learning approach.

Journal of neural engineering Jan 31, 2019
OBJECTIVE: Sedation of neurocritically ill patients is one of the most challenging situation in ICUs. Quantitative knowledge on the sedation effect on brain activity in that complex scenario could help to uncover new markers for sedation assessment. ...
Intraoperative Neurophysiological Monitoring Propofol Brain Injuries Dose-Response Relationship, Drug Hypnotics and Sedatives Female Adult Male Middle Aged Cohort Studies Infusions, Intravenous Electroencephalography Critical Care Midazolam Humans Machine Learning Prospective Studies
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Artificial intelligence in the intensive care unit.

Critical care (London, England) Jan 10, 2019
Humans Artificial Intelligence Decision Support Techniques Intensive Care Units Critical Care
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Machine Learning-Based Prediction of Clinical Outcomes for Children During Emergency Department Triage.

JAMA network open Jan 4, 2019
IMPORTANCE: While machine learning approaches may enhance prediction ability, little is known about their utility in emergency department (ED) triage.
Machine Learning Prognosis Female Hospitalization Male Humans Critical Care Outcomes Models, Educational Child, Hospitalized Predictive Value of Tests Adolescent Triage Child, Preschool Emergency Service, Hospital Child Critical Care United States Quality Improvement
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Big Data Analysis and Machine Learning in Intensive Care Units.

Medicina intensiva Dec 24, 2018
Intensive care is an ideal environment for the use of Big Data Analysis (BDA) and Machine Learning (ML), due to the huge amount of information processed and stored in electronic format in relation to such care. These tools can improve our clinical re...
Humans Critical Care Machine Learning Information Dissemination Data Analysis Information Storage and Retrieval Databases, Factual Retrospective Studies Intensive Care Units Big Data Electronic Health Records Randomized Controlled Trials as Topic Natural Language Processing Data Anonymization
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Ensuring Fairness in Machine Learning to Advance Health Equity.

Annals of internal medicine Dec 4, 2018
Machine learning is used increasingly in clinical care to improve diagnosis, treatment selection, and health system efficiency. Because machine-learning models learn from historically collected data, populations that have experienced human and struct...
Length of Stay Social Justice Health Equity Healthcare Disparities Critical Care Patient Outcome Assessment Health Care Rationing Humans Machine Learning
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Machine learning in critical care: state-of-the-art and a sepsis case study.

Biomedical engineering online Nov 20, 2018
BACKGROUND: Like other scientific fields, such as cosmology, high-energy physics, or even the life sciences, medicine and healthcare face the challenge of an extremely quick transformation into data-driven sciences. This challenge entails the dauntin...
Machine Learning Software Data Analysis Prospective Studies Prognosis Humans Artificial Intelligence Intensive Care Units Expert Systems Reproducibility of Results Medical Informatics Sepsis Computer Graphics Probability Critical Care
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Deep learning algorithms to identify documentation of serious illness conversations during intensive care unit admissions.

Palliative medicine Nov 14, 2018
Guidelines as Topic Humans Boston Algorithms Admitting Department, Hospital Health Personnel Male Intensive Care Units Middle Aged Female Deep Learning Adult Critical Care Documentation
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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 ...
APACHE Patient Admission Middle Aged Risk Assessment Intensive Care Units Humans Decision Support Systems, Clinical Sepsis Clinical Decision-Making Machine Learning Hospital Mortality Female Logistic Models Prognosis ROC Curve Feasibility Studies Retrospective Studies Aged Critical Care Male Datasets as Topic
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Applying machine learning to continuously monitored physiological data.

Journal of clinical monitoring and computing Nov 11, 2018
The use of machine learning (ML) in healthcare has enormous potential for improving disease detection, clinical decision support, and workflow efficiencies. In this commentary, we review published and potential applications for the use of ML for moni...
Humans Machine Learning Software Algorithms Databases, Factual Intensive Care Units Electronic Health Records Randomized Controlled Trials as Topic Adult Expert Systems Delirium Respiration, Artificial Wavelet Analysis Arrhythmias, Cardiac Sepsis Clinical Alarms Decision Support Systems, Clinical Atrial Fibrillation Monitoring, Physiologic Critical Care
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