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Critical Care

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Drivers of Prolonged Hospitalization Following Spine Surgery: A Game-Theory-Based Approach to Explaining Machine Learning Models.

The Journal of bone and joint surgery. American volume Jan 6, 2021
BACKGROUND: Understanding the interactions between variables that predict prolonged hospital length of stay (LOS) following spine surgery can help uncover drivers of this risk in patients. This study utilized a novel game-theory-based approach to dev...
Risk Factors Male Middle Aged Comorbidity Computer Simulation Intensive Care Units Female Nervous System Diseases Spinal Diseases Game Theory Medicaid Length of Stay United States Elective Surgical Procedures Critical Care Humans Machine Learning
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[What is new… Implementation of artificial intelligence in intensive care medicine : Hype or already reality?].

Der Anaesthesist Jan 1, 2021
Humans Artificial Intelligence Algorithms Medicine Critical Care
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[Artificial intelligence provides promotion of big data in medical work and contribution to people's health as soon as possible: real-time warning of critical illness is the pioneer of artificial intelligence in clinical medicine].

Zhonghua wei zhong bing ji jiu yi xue Oct 1, 2020
Through the big data intelligent algorithm and application of artificial intelligence in critically ill patients, the value of the combination of clinical real-time warning and artificial intelligence in critical care medicine was explored. Artificia...
Big Data Critical Care Humans Artificial Intelligence Critical Illness
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A Time-Phased Machine Learning Model for Real-Time Prediction of Sepsis in Critical Care.

Critical care medicine Oct 1, 2020
OBJECTIVES: As a life-threatening condition, sepsis is one of the major public health issues worldwide. Early prediction can improve sepsis outcomes with appropriate interventions. With the PhysioNet/Computing in Cardiology Challenge 2019, we aimed t...
Vital Signs Retrospective Studies Intensive Care Units Reproducibility of Results Severity of Illness Index Sepsis Time Factors Critical Care Early Diagnosis Humans Machine Learning
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A statistically rigorous deep neural network approach to predict mortality in trauma patients admitted to the intensive care unit.

The journal of trauma and acute care surgery Oct 1, 2020
BACKGROUND: Trauma patients admitted to critical care are at high risk of mortality because of their injuries. Our aim was to develop a machine learning-based model to predict mortality using Fahad-Liaqat-Ahmad Intensive Machine (FLAIM) framework. We...
Machine Learning Prognosis Retrospective Studies Critical Illness Humans Neural Networks, Computer Adult Male Middle Aged Sepsis Intensive Care Units Female Hospitalization Young Adult Wounds and Injuries Proportional Hazards Models ROC Curve Multivariate Analysis Sodium Injury Severity Score Critical Care Organ Dysfunction Scores
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Practical Machine Learning-Based Sepsis Prediction.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2020
Sepsis is a life-threatening clinical syndrome and one of the most expensive conditions treated in hospitals. It is challenging to detect due to the nonspecific clinical signs and the absence of gold standard diagnostics. However, early recognition o...
Critical Care Humans Machine Learning Sepsis
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Predictive Modeling of Pressure Injury Risk in Patients Admitted to an Intensive Care Unit.

American journal of critical care : an official publication, American Association of Critical-Care Nurses Jul 1, 2020
BACKGROUND: Pressure injuries are an important problem in hospital care. Detecting the population at risk for pressure injuries is the first step in any preventive strategy. Available tools such as the Norton and Braden scales do not take into accoun...
Humans Machine Learning Intensive Care Units Electronic Health Records Female Risk Factors Aged Adolescent Child Hospitals, University Hemoglobins Data Mining Critical Care Sensitivity and Specificity APACHE Male Pressure Ulcer Middle Aged Aged, 80 and over Risk Assessment Young Adult Adult
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Blood Lactate Concentration Prediction in Critical Care.

Studies in health technology and informatics Jun 16, 2020
Blood lactate concentration is a reliable risk indicator of deterioration in critical care requiring frequent blood sampling. However, lactate measurement is an invasive procedure that can increase risk of infections. Yet there is no clinical consens...
Humans Machine Learning Algorithms Risk Factors Critical Care Lactic Acid
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Machine Learning and Artificial Intelligence in Pediatric Research: Current State, Future Prospects, and Examples in Perioperative and Critical Care.

The Journal of pediatrics Jun 1, 2020
Blood Transfusion Artificial Intelligence Biomedical Research Humans Critical Care Risk Assessment Machine Learning Perioperative Care Patient Admission Intraoperative Complications Postoperative Complications Ultrasonography Heart Arrest Monitoring, Intraoperative Hospital Mortality Airway Management Intensive Care Units, Pediatric Hemorrhage Anesthesia Algorithms
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Augmented intelligence in pediatric anesthesia and pediatric critical care.

Current opinion in anaesthesiology Jun 1, 2020
PURPOSE OF REVIEW: Acute care technologies, including novel monitoring devices, big data, increased computing capabilities, machine-learning algorithms and automation, are converging. This enables the application of augmented intelligence for improve...
Anesthesia Child Intelligence Critical Care Humans Artificial Intelligence Machine Learning
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