AIMC Topic: Sepsis

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Safety-driven design of machine learning for sepsis treatment.

Journal of biomedical informatics Mar 30, 2021
Machine learning (ML) has the potential to bring significant clinical benefits. However, there are patient safety challenges in introducing ML in complex healthcare settings and in assuring the technology to the satisfaction of the different regulato...
Machine Learning Delivery of Health Care Sepsis Workflow Humans
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Prediction of Sepsis in COVID-19 Using Laboratory Indicators.

Frontiers in cellular and infection microbiology Mar 2, 2021
BACKGROUND: The outbreak of coronavirus disease 2019 (COVID-19) has become a global public health concern. Many inpatients with COVID-19 have shown clinical symptoms related to sepsis, which will aggravate the deterioration of patients' condition. We...
Humans Adult Logistic Models Machine Learning SARS-CoV-2 China COVID-19 Testing Male Retrospective Studies Sepsis Risk Factors COVID-19 Middle Aged Female ROC Curve Prognosis Aged
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Machine Learning Identifies Complicated Sepsis Course and Subsequent Mortality Based on 20 Genes in Peripheral Blood Immune Cells at 24 H Post-ICU Admission.

Frontiers in immunology Feb 22, 2021
A complicated clinical course for critically ill patients admitted to the intensive care unit (ICU) usually includes multiorgan dysfunction and subsequent death. Owing to the heterogeneity, complexity, and unpredictability of the disease progression,...
Chromosome Mapping Leukocytes Critical Care Intensive Care Units Disease Susceptibility Reproducibility of Results ROC Curve Gene Expression Profiling Humans Computational Biology Time Factors Machine Learning Databases, Genetic Hospital Mortality Transcriptome Biomarkers Sepsis
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HeMA: A hierarchically enriched machine learning approach for managing false alarms in real time: A sepsis prediction case study.

Computers in biology and medicine Feb 17, 2021
Early detection of sepsis can be life-saving. Machine learning models have shown great promise in early sepsis prediction when applied to patient physiological data in real-time. However, these existing models often under-perform in terms of positive...
Humans Machine Learning Sepsis Predictive Value of Tests Early Diagnosis
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DeepAISE - An interpretable and recurrent neural survival model for early prediction of sepsis.

Artificial intelligence in medicine Feb 13, 2021
Sepsis, a dysregulated immune system response to infection, is among the leading causes of morbidity, mortality, and cost overruns in the Intensive Care Unit (ICU). Early prediction of sepsis can improve situational awareness among clinicians and fac...
Critical Care Intensive Care Units Sepsis Humans Artificial Intelligence Area Under Curve
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Artificial intelligence in sepsis early prediction and diagnosis using unstructured data in healthcare.

Nature communications Jan 29, 2021
Sepsis is a leading cause of death in hospitals. Early prediction and diagnosis of sepsis, which is critical in reducing mortality, is challenging as many of its signs and symptoms are similar to other less critical conditions. We develop an artifici...
ROC Curve Predictive Value of Tests Feasibility Studies Severity of Illness Index Sepsis Time Factors Data Mining Early Diagnosis Clinical Decision Rules Humans Machine Learning Risk Assessment Prevalence Intensive Care Units Electronic Health Records
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Is Deep Reinforcement Learning Ready for Practical Applications in Healthcare? A Sensitivity Analysis of Duel-DDQN for Hemodynamic Management in Sepsis Patients.

AMIA ... Annual Symposium proceedings. AMIA Symposium Jan 25, 2021
The potential of Reinforcement Learning (RL) has been demonstrated through successful applications to games such as Go and Atari. However, while it is straightforward to evaluate the performance of an RL algorithm in a game setting by simply using it...
Deep Learning Sepsis Humans Reinforcement, Psychology Delivery of Health Care Algorithms Learning Hemodynamics
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Predicting Volume Responsiveness Among Sepsis Patients Using Clinical Data and Continuous Physiological Waveforms.

AMIA ... Annual Symposium proceedings. AMIA Symposium Jan 25, 2021
The efficacy of early fluid treatment in patients with sepsis is unclear and may contribute to serious adverse events due to fluid non-responsiveness. The current method of deciding if patients are responsive to fluid administration is often subjecti...
Fluid Therapy Middle Aged Sepsis Humans Logistic Models Machine Learning Male
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Contextual Embeddings from Clinical Notes Improves Prediction of Sepsis.

AMIA ... Annual Symposium proceedings. AMIA Symposium Jan 25, 2021
Sepsis, a life-threatening organ dysfunction, is a clinical syndrome triggered by acute infection and affects over 1 million Americans every year. Untreated sepsis can progress to septic shock and organ failure, making sepsis one of the leading cause...
Humans Algorithms Electronic Health Records Clinical Decision Rules Deep Learning Language Sepsis Decision Support Systems, Clinical Severity of Illness Index Shock, Septic Natural Language Processing
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A comparison of machine learning models versus clinical evaluation for mortality prediction in patients with sepsis.

PloS one Jan 19, 2021
INTRODUCTION: Patients with sepsis who present to an emergency department (ED) have highly variable underlying disease severity, and can be categorized from low to high risk. Development of a risk stratification tool for these patients is important f...
Humans Machine Learning Retrospective Studies Female Sepsis Hospital Mortality Predictive Value of Tests Emergency Service, Hospital Models, Biological Male Middle Aged Severity of Illness Index Risk Factors Aged Aged, 80 and over
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