AIMC Topic: Intensive Care Units, Pediatric

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[Application of the artificial intelligence-rapid whole-genome sequencing diagnostic system in the neonatal/pediatric intensive care unit].

Zhongguo dang dai er ke za zhi = Chinese journal of contemporary pediatrics May 1, 2021
Pediatric patients in the neonatal intensive care unit (NICU) and the pediatric intensive care unit (PICU) have a high incidence rate of genetic diseases, and early rapid etiological diagnosis and targeted interventions can help to reduce mortality o...
Humans Child Intensive Care Units, Pediatric Whole Genome Sequencing Intensive Care Units, Neonatal Artificial Intelligence Critical Illness Infant, Newborn
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Potential Prognostic Markers in the Heart Rate Variability Features for Early Diagnosis of Sepsis in the Pediatric Intensive Care Unit using Convolutional Neural Network Classifiers.

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
Blood infection due to different circumstances could immediately develop to an extreme body reaction that leads to a serious life-threatening condition, called Sepsis. Currently, therapeutic protocols through timely antibiotic resuscitation strategie...
Prognosis Humans Sepsis Intensive Care Units, Pediatric Neural Networks, Computer Child Heart Rate Early Diagnosis
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Potential Prognostic Markers in the Heart Rate Variability Features for Early Diagnosis of Sepsis in the Pediatric Intensive Care Unit using Convolutional Neural Network Classifiers.

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
Blood infection due to different circumstances could immediately develop to an extreme body reaction that leads to a serious life-threatening condition, called Sepsis. Currently, therapeutic protocols through timely antibiotic resuscitation strategie...
Heart Rate Early Diagnosis Sepsis Child Intensive Care Units, Pediatric Humans Neural Networks, Computer Prognosis
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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
Intensive Care Units, Pediatric Blood Transfusion Critical Care Monitoring, Intraoperative Ultrasonography Hospital Mortality Intraoperative Complications Heart Arrest Airway Management Hemorrhage Anesthesia Patient Admission Artificial Intelligence Machine Learning Algorithms Biomedical Research Risk Assessment Postoperative Complications Humans Perioperative Care
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Artificial Intelligence: Progress Towards an Intelligent Clinical Support System.

Pediatric critical care medicine : a journal of the Society of Critical Care Medicine and the World Federation of Pediatric Intensive and Critical Care Societies Apr 1, 2019
Child Intensive Care Units, Pediatric Humans Artificial Intelligence Sepsis
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Predicting individual physiologically acceptable states at discharge from a pediatric intensive care unit.

Journal of the American Medical Informatics Association : JAMIA Dec 1, 2018
OBJECTIVE: Quantify physiologically acceptable PICU-discharge vital signs and develop machine learning models to predict these values for individual patients throughout their PICU episode.
Child Intensive Care Units, Pediatric Regression Analysis Patient Discharge Reference Values Infant Vital Signs Humans Adolescent Neural Networks, Computer Child, Preschool Machine Learning
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Artificial Intelligence: An Inkling of Caution.

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
Artificial Intelligence Sepsis Intensive Care Units, Pediatric Child Humans
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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.
Logistic Models Monitoring, Physiologic Predictive Value of Tests Heart Rate Machine Learning Organ Dysfunction Scores Humans Respiratory Rate Prospective Studies Adolescent Artificial Intelligence Male Female Child Case-Control Studies Intensive Care Units, Pediatric Sepsis
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Applying Machine Learning to Pediatric Critical Care Data.

Pediatric critical care medicine : a journal of the Society of Critical Care Medicine and the World Federation of Pediatric Intensive and Critical Care Societies Jul 1, 2018
OBJECTIVES: To explore whether machine learning applied to pediatric critical care data could discover medically pertinent information, we analyzed clinically collected electronic medical record data, after data extraction and preparation, using k-me...
Critical Care Machine Learning Information Dissemination Electronic Health Records Intensive Care Units, Pediatric
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Learning Healthcare Systems in Pediatrics: Cross-Institutional and Data-Driven Decision-Support for Intensive Care Environments (CADDIE).

Studies in health technology and informatics Jan 1, 2018
BACKGROUND: The vast amount of data generated in healthcare can be reused to support decision-making by developing clinical decision-support systems. Since evidence is lacking in Pediatrics, it seems to be beneficial to design future systems towards ...
Data Collection Child Critical Care Intensive Care Units, Pediatric Humans Decision Support Systems, Clinical Pediatrics Machine Learning Algorithms
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