AIMC Topic: Organ Dysfunction Scores

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Applying Artificial Intelligence to Identify Physiomarkers Predicting Severe Sepsis in the PICU.

Pediatric critical care medicine : a journal of the Society of Critical Care Medicine and the World Federation of Pediatric Intensive and Critical Care Societies Oct 1, 2018
OBJECTIVES: We used artificial intelligence to develop a novel algorithm using physiomarkers to predict the onset of severe sepsis in critically ill children.
Adolescent Child Intensive Care Units, Pediatric Case-Control Studies Sepsis Heart Rate Organ Dysfunction Scores Respiratory Rate Monitoring, Physiologic Artificial Intelligence Predictive Value of Tests Machine Learning Logistic Models Female Male Prospective Studies Humans
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[Comparison of machine learning method and logistic regression model in prediction of acute kidney injury in severely burned patients].

Zhonghua shao shang za zhi = Zhonghua shaoshang zazhi = Chinese journal of burns Jun 20, 2018
To build risk prediction models for acute kidney injury (AKI) in severely burned patients, and to compare the prediction performance of machine learning method and logistic regression model. The clinical data of 157 severely burned patients in Augu...
Humans Machine Learning Sepsis ROC Curve Logistic Models Hospitalization Sensitivity and Specificity Acute Kidney Injury Organ Dysfunction Scores Fluid Therapy Explosions Burns
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An Interpretable Machine Learning Model for Accurate Prediction of Sepsis in the ICU.

Critical care medicine Apr 1, 2018
OBJECTIVES: Sepsis is among the leading causes of morbidity, mortality, and cost overruns in critically ill patients. Early intervention with antibiotics improves survival in septic patients. However, no clinically validated system exists for real-ti...
Vital Signs Time-to-Treatment Organ Dysfunction Scores Age Factors Blood Pressure Sex Factors Humans Academic Medical Centers Heart Rate Machine Learning Decision Support Systems, Clinical Socioeconomic Factors Electrocardiography Hospital Mortality Middle Aged ROC Curve Comorbidity Critical Illness Electronic Health Records Male Female Intensive Care Units Severity of Illness Index Aged Sepsis Time Factors
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Cell Free DNA and Procalcitonin as Early Markers of Complications in ICU Patients with Multiple Trauma and Major Surgery.

Clinical laboratory Dec 1, 2016
BACKGROUND: Cell free DNA (cfDNA) was recently suggested as a new marker of sepsis and poor outcome in ICU patients. Procalcitonin has also been the focus of attention as an early marker for systemic inflammation and sepsis.
Injury Severity Score Organ Dysfunction Scores Reproducibility of Results Sepsis Calcitonin Time Factors Risk Factors Prognosis Humans Hospital Mortality Early Diagnosis Male Area Under Curve Postoperative Complications Biomarkers Adult DNA Surgical Procedures, Operative Intensive Care Units Middle Aged Length of Stay ROC Curve Female Lactic Acid Cell-Free Nucleic Acids Predictive Value of Tests Multiple Trauma C-Reactive Protein
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