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Organ Dysfunction Scores

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Low vitamin D at ICU admission is associated with cancer, infections, acute respiratory insufficiency, and liver failure.

Nutrition (Burbank, Los Angeles County, Calif.) 30682545
OBJECTIVES: Vitamin D deficiency may be associated with comorbidities and poor prognosis. However, this association in patients in the intensive care unit (ICU) has not been fully elucidated. The aim of this study was to investigate whether the serum...
Acute Disease Adult Aged APACHE C-Reactive Protein Comorbidity Critical Illness Cross-Sectional Studies Female Hospital Mortality Humans Infections Intensive Care Units Liver Failure Male Middle Aged Neoplasms Organ Dysfunction Scores Patient Admission Prognosis Respiration, Artificial Respiratory Insufficiency Severity of Illness Index Time Factors Vitamin D Vitamin D Deficiency
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DeepSOFA: A Continuous Acuity Score for Critically Ill Patients using Clinically Interpretable Deep Learning.

Scientific reports 30755689
Traditional methods for assessing illness severity and predicting in-hospital mortality among critically ill patients require time-consuming, error-prone calculations using static variable thresholds. These methods do not capitalize on the emerging a...
Adolescent Adult Aged Area Under Curve Critical Care Critical Illness Databases, Factual Decision Making Deep Learning Female Hospital Mortality Humans Intensive Care Units Length of Stay Longitudinal Studies Male Middle Aged Organ Dysfunction Scores Probability Retrospective Studies Severity of Illness Index Young Adult
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Heart rate variability based machine learning models for risk prediction of suspected sepsis patients in the emergency department.

Medicine 30732136
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...
Aged Aged, 80 and over Emergency Service, Hospital Female Heart Rate Hospital Mortality Humans Machine Learning Male Middle Aged Organ Dysfunction Scores Reproducibility of Results ROC Curve Sepsis Severity of Illness Index Singapore Socioeconomic Factors Systemic Inflammatory Response Syndrome Triage
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ICU staffing feature phenotypes and their relationship with patients' outcomes: an unsupervised machine learning analysis.

Intensive care medicine 31595349
PURPOSE: To study whether ICU staffing features are associated with improved hospital mortality, ICU length of stay (LOS) and duration of mechanical ventilation (MV) using cluster analysis directed by machine learning.
Brazil Cluster Analysis Hospital Bed Capacity Hospital Mortality Humans Intensive Care Units Length of Stay Logistic Models Nurses Odds Ratio Organ Dysfunction Scores Personnel Staffing and Scheduling Physical Therapists Physicians Retrospective Studies Time Factors Unsupervised Machine Learning
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On classifying sepsis heterogeneity in the ICU: insight using machine learning.

Journal of the American Medical Informatics Association : JAMIA 31951005
OBJECTIVES: Current machine learning models aiming to predict sepsis from electronic health records (EHR) do not account 20 for the heterogeneity of the condition despite its emerging importance in prognosis and treatment. This work demonstrates the ...
Diagnosis, Differential Electronic Health Records Humans Intensive Care Units Machine Learning Organ Dysfunction Scores Sensitivity and Specificity Sepsis
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Machine learning algorithm to predict mortality in patients undergoing continuous renal replacement therapy.

Critical care (London, England) 32028984
BACKGROUND: Previous scoring models such as the Acute Physiologic Assessment and Chronic Health Evaluation II (APACHE II) and the Sequential Organ Failure Assessment (SOFA) scoring systems do not adequately predict mortality of patients undergoing co...
Acute Kidney Injury Aged Aged, 80 and over Algorithms APACHE Area Under Curve Continuous Renal Replacement Therapy Female Humans Machine Learning Male Middle Aged Mortality Organ Dysfunction Scores Republic of Korea Risk Factors ROC Curve Severity of Illness Index
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Automated quantification and architectural pattern detection of hepatic fibrosis in NAFLD.

Annals of diagnostic pathology 32531442
Accurate detection and quantification of hepatic fibrosis remain essential for assessing the severity of non-alcoholic fatty liver disease (NAFLD) and its response to therapy in clinical practice and research studies. Our aim was to develop an integr...
Artificial Intelligence Automation Azo Compounds Biopsy Clinical Trials as Topic Collagen Eosine Yellowish-(YS) Fibrosis Humans Image Processing, Computer-Assisted Liver Liver Cirrhosis Methyl Green Non-alcoholic Fatty Liver Disease Organ Dysfunction Scores Pathologists Portal Vein Practice Patterns, Physicians' Severity of Illness Index Supervised Machine Learning
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Supervised classification techniques for prediction of mortality in adult patients with sepsis.

The American journal of emergency medicine 33036848
BACKGROUND: Sepsis mortality is still unacceptably high and an appropriate prognostic tool may increase the accuracy for clinical decisions.
Aged Artificial Intelligence Colombia Decision Making Emergency Service, Hospital Female Hospital Mortality Hospitals, University Humans Male Middle Aged Organ Dysfunction Scores Predictive Value of Tests Prognosis Prospective Studies Sepsis
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A deep learning approach for sepsis monitoring via severity score estimation.

Computer methods and programs in biomedicine 33157471
BACKGROUND AND OBJECTIVE: Sepsis occurs in response to an infection in the body and can progress to a fatal stage. Detection and monitoring of sepsis require multi-step analysis, which is time-consuming, costly and requires medically trained personne...
Deep Learning Humans Intensive Care Units Organ Dysfunction Scores Prognosis Retrospective Studies ROC Curve Sepsis
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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 32773672
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...
Adult Critical Care Critical Illness Female Hospitalization Humans Injury Severity Score Intensive Care Units Machine Learning Male Middle Aged Multivariate Analysis Neural Networks, Computer Organ Dysfunction Scores Prognosis Proportional Hazards Models Retrospective Studies ROC Curve Sepsis Sodium Wounds and Injuries Young Adult
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