AIMC Topic: Sepsis

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FedDSS: A data-similarity approach for client selection in horizontal federated learning.

International journal of medical informatics Oct 16, 2024
BACKGROUND AND OBJECTIVE: Federated learning (FL) is an emerging distributed learning framework allowing multiple clients (hospitals, institutions, smart devices, etc.) to collaboratively train a centralized machine learning model without disclosing ...
Algorithms Sepsis Child Humans Machine Learning
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Machine learning interpretability methods to characterize the importance of hematologic biomarkers in prognosticating patients with suspected infection.

Computers in biology and medicine Oct 12, 2024
OBJECTIVE: To evaluate the effectiveness of Monocyte Distribution Width (MDW) in predicting sepsis outcomes in emergency department (ED) patients compared to other hematologic parameters and vital signs, and to determine whether routine parameters co...
Humans Adult Male Middle Aged Sepsis Retrospective Studies Machine Learning Female Biomarkers Aged Prognosis
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Development and validation of a sepsis risk index supporting early identification of ICU-acquired sepsis: an observational study.

Anaesthesia, critical care & pain medicine Oct 2, 2024
BACKGROUND: Sepsis is a threat to global health, and domestically is the major cause of in-hospital mortality. Due to increases in inpatient morbidity and mortality resulting from sepsis, healthcare providers (HCPs) would accrue significant benefits ...
Sensitivity and Specificity Male Middle Aged Machine Learning Risk Assessment Intensive Care Units Shock, Septic Female Humans Critical Care Sepsis Aged Early Diagnosis Hospital Mortality Adult Cross Infection ROC Curve
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Transfer learning-enabled outcome prediction for guiding CRRT treatment of the pediatric patients with sepsis.

BMC medical informatics and decision making Sep 27, 2024
Continuous renal replacement therapy (CRRT) is a life-saving procedure for sepsis but the benefit of CRRT varies and prediction of clinical outcomes is valuable in efficient treatment planning. This study aimed to use machine learning (ML) models tra...
Humans Child, Preschool Male Child Infant Machine Learning Sepsis Continuous Renal Replacement Therapy Adolescent Female
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Machine learning reveals the rules governing the efficacy of mesenchymal stromal cells in septic preclinical models.

Stem cell research & therapy Sep 11, 2024
BACKGROUND: Mesenchymal Stromal Cells (MSCs) are the preferred candidates for therapeutics as they possess multi-directional differentiation potential, exhibit potent immunomodulatory activity, are anti-inflammatory, and can function like antimicrobi...
Mesenchymal Stem Cells Mesenchymal Stem Cell Transplantation Machine Learning Animals Sepsis Humans
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Machine learning-based prognostic model for 30-day mortality prediction in Sepsis-3.

BMC medical informatics and decision making Sep 9, 2024
BACKGROUND: Sepsis poses a critical threat to hospitalized patients, particularly those in the Intensive Care Unit (ICU). Rapid identification of Sepsis is crucial for improving survival rates. Machine learning techniques offer advantages over tradit...
Humans Prognosis Intensive Care Units Machine Learning Biomarkers Middle Aged Sepsis Female Nomograms Aged Male
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Predicting Mortality in Sepsis-Associated Acute Respiratory Distress Syndrome: A Machine Learning Approach Using the MIMIC-III Database.

Journal of intensive care medicine Sep 5, 2024
BackgroundTo develop and validate a mortality prediction model for patients with sepsis-associated Acute Respiratory Distress Syndrome (ARDS).MethodsThis retrospective cohort study included 2466 patients diagnosed with sepsis and ARDS within 24 h of ...
Hospital Mortality Humans Respiratory Distress Syndrome ROC Curve Predictive Value of Tests Machine Learning Logistic Models Bayes Theorem Databases, Factual Male Female Retrospective Studies Middle Aged Aged Intensive Care Units Sepsis
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Enhancing Patient Selection in Sepsis Clinical Trials Design Through an AI Enrichment Strategy: Algorithm Development and Validation.

Journal of medical Internet research Sep 4, 2024
BACKGROUND: Sepsis is a heterogeneous syndrome, and enrollment of more homogeneous patients is essential to improve the efficiency of clinical trials. Artificial intelligence (AI) has facilitated the identification of homogeneous subgroups, but how t...
Middle Aged Sepsis Patient Selection Female Aged Male Clinical Trials as Topic Algorithms Retrospective Studies Humans Artificial Intelligence
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Prediction of sepsis mortality in ICU patients using machine learning methods.

BMC medical informatics and decision making Aug 16, 2024
PROBLEM: Sepsis, a life-threatening condition, accounts for the deaths of millions of people worldwide. Accurate prediction of sepsis outcomes is crucial for effective treatment and management. Previous studies have utilized machine learning for prog...
Adult Male Intensive Care Units Middle Aged Humans Sepsis Machine Learning Female Prognosis Aged
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Distinguishing neonatal culture-negative sepsis from rule-out sepsis with artificial intelligence-derived graphs.

Pediatric research Aug 15, 2024
Novel artificial intelligence methods can aide in identification of cases of conditions using only unstructured electronic health record data. This graph-based method compares comprehensive electronic health records among neonates using temporal data...
Blood Culture Neonatal Sepsis Female Infant, Newborn Sepsis Artificial Intelligence Electronic Health Records Humans
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