AIMC Topic: Sepsis

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Heart rate variability based machine learning models for risk prediction of suspected sepsis patients in the emergency department.

Medicine Feb 1, 2019
Early identification of high-risk septic patients in the emergency department (ED) may guide appropriate management and disposition, thereby improving outcomes. We compared the performance of machine learning models against conventional risk stratifi...
Middle Aged Severity of Illness Index Sepsis Hospital Mortality Aged Aged, 80 and over Male Emergency Service, Hospital Singapore Heart Rate Organ Dysfunction Scores Systemic Inflammatory Response Syndrome ROC Curve Socioeconomic Factors Triage Humans Machine Learning Female Reproducibility of Results
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Artificial Intelligence Tools for Sepsis and Cancer.

JAMA Dec 11, 2018
Neoplasms Humans Sepsis Artificial Intelligence Decision Making, Computer-Assisted
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The role of presepsin in the diagnosis and assessment of severity of sepsis and severe pneumonia.

Terapevticheskii arkhiv Nov 22, 2018
AIM: The aim of this study was to evaluate marker of inflammation presepsin to improve diagnosis of severe pneumonia, sepsis.
Adolescent Pneumonia Peptide Fragments Young Adult Humans Lipopolysaccharide Receptors Adult Biomarkers Middle Aged Aged Sepsis
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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
Sepsis Child Intensive Care Units, Pediatric Humans Artificial Intelligence
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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.
Humans Artificial Intelligence Machine Learning Prospective Studies Adolescent Child Intensive Care Units, Pediatric Logistic Models Female Male Case-Control Studies Sepsis Organ Dysfunction Scores Monitoring, Physiologic Respiratory Rate Predictive Value of Tests Heart Rate
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Early Prediction of Sepsis in EMR Records Using Traditional ML Techniques and Deep Learning LSTM Networks.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2018
Sepsis is a life-threatening condition caused by infection and subsequent overreaction by the immune system. Physicians effectively treat sepsis with early administration of antibiotics. However, excessive use of antibiotics on false positive cases c...
Neural Networks, Computer Machine Learning Electronic Health Records Deep Learning Sepsis 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...
Burns Organ Dysfunction Scores Explosions ROC Curve Logistic Models Fluid Therapy Humans Machine Learning Acute Kidney Injury Hospitalization Sensitivity and Specificity Sepsis
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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...
Severity of Illness Index Sepsis Time Factors Hospital Mortality ROC Curve Decision Support Systems, Clinical Socioeconomic Factors Humans Aged Machine Learning Male Critical Illness Organ Dysfunction Scores Middle Aged Intensive Care Units Vital Signs Comorbidity Heart Rate Electronic Health Records Electrocardiography Sex Factors Female Age Factors Academic Medical Centers Blood Pressure Time-to-Treatment
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[Ulinastatin attenuates hyper-permeability of vascular endothelialium cells induced by serum from patients with sepsis].

Xi bao yu fen zi mian yi xue za zhi = Chinese journal of cellular and molecular immunology Dec 1, 2017
Objective To study the effect of ulinastatin (UTI) on the hyper-permeability of human umbilical vein endothelial cell induced by the serum from patients with severe sepsis. Methods The serum level of tumor necrosis factor α (TNF-α) was examined by EL...
Glycoproteins Humans Human Umbilical Vein Endothelial Cells Tumor Necrosis Factor-alpha Serum Capillary Permeability Sepsis
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A Case Study on Sepsis Using PubMed and Deep Learning for Ontology Learning.

Studies in health technology and informatics Jan 1, 2017
We investigate the application of distributional semantics models for facilitating unsupervised extraction of biomedical terms from unannotated corpora. Term extraction is used as the first step of an ontology learning process that aims to (semi-)aut...
Humans Machine Learning Sepsis Semantics Natural Language Processing PubMed Information Storage and Retrieval
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