AIMC Topic: Sepsis
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Development and external validation of machine learning-based models to predict patients with cellulitis developing sepsis during hospitalisation.
BMJ open
Jul 5, 2024
OBJECTIVE: Cellulitis is the most common cause of skin-related hospitalisations, and the mortality of patients with sepsis remains high. Some stratification models have been developed, but their performance in external validation has been unsatisfact...
Evaluating Explanations From AI Algorithms for Clinical Decision-Making: A Social Science-Based Approach.
IEEE journal of biomedical and health informatics
Jul 2, 2024
Explainable Artificial Intelligence (XAI) techniques generate explanations for predictions from AI models. These explanations can be evaluated for (i) faithfulness to the prediction, i.e., its correctness about the reasons for prediction, and (ii) us...
Integrated multi-omics analysis and machine learning developed diagnostic markers and prognostic model based on Efferocytosis-associated signatures for septic cardiomyopathy.
Clinical immunology (Orlando, Fla.)
Jun 27, 2024
Septic cardiomyopathy (SCM) is characterized by an abnormal inflammatory response and increased mortality. The role of efferocytosis in SCM is not well understood. We used integrated multi-omics analysis to explore the clinical and genetic roles of e...
Sepsis mortality prediction with Machine Learning Tecniques.
Medicina intensiva
Jun 13, 2024
OBJECTIVE: To develop a sepsis death classification model based on machine learning techniques for patients admitted to the Intensive Care Unit (ICU).
Unraveling the genetic and molecular landscape of sepsis and acute kidney injury: A comprehensive GWAS and machine learning approach.
International immunopharmacology
Jun 8, 2024
OBJECTIVES: This study aimed to explore the underlying mechanisms of sepsis and acute kidney injury (AKI), including sepsis-associated AKI (SA-AKI), a frequent complication in critically ill sepsis patients.
Random forest differentiation of Escherichia coli in elderly sepsis using biomarkers and infectious sites.
Scientific reports
Jun 5, 2024
This study addresses the challenge of accurately diagnosing sepsis subtypes in elderly patients, particularly distinguishing between Escherichia coli (E. coli) and non-E. coli infections. Utilizing machine learning, we conducted a retrospective analy...
Deciphering Abnormal Platelet Subpopulations in COVID-19, Sepsis and Systemic Lupus Erythematosus through Machine Learning and Single-Cell Transcriptomics.
International journal of molecular sciences
May 29, 2024
This study focuses on understanding the transcriptional heterogeneity of activated platelets and its impact on diseases such as sepsis, COVID-19, and systemic lupus erythematosus (SLE). Recognizing the limited knowledge in this area, our research aim...
Identification of Marker Genes in Infectious Diseases from ScRNA-seq Data Using Interpretable Machine Learning.
International journal of molecular sciences
May 29, 2024
A common result of infection is an abnormal immune response, which may be detrimental to the host. To control the infection, the immune system might undergo regulation, therefore producing an excess of either pro-inflammatory or anti-inflammatory pat...
A scoping review of machine learning for sepsis prediction- feature engineering strategies and model performance: a step towards explainability.
Critical care (London, England)
May 28, 2024
BACKGROUND: Sepsis, an acute and potentially fatal systemic response to infection, significantly impacts global health by affecting millions annually. Prompt identification of sepsis is vital, as treatment delays lead to increased fatalities through ...
Screening and Identification of Neutrophil Extracellular Trap-related Diagnostic Biomarkers for Pediatric Sepsis by Machine Learning.
Inflammation
May 25, 2024
Neutrophil extracellular trap (NET) is released by neutrophils to trap invading pathogens and can lead to dysregulation of immune responses and disease pathogenesis. However, systematic evaluation of NET-related genes (NETRGs) for the diagnosis of pe...
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