Critical Care

Sepsis

Latest AI and machine learning research in sepsis for healthcare professionals.

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Critical-Care Subcategories: Sepsis
Showing 211-231 of 9,027 articles
CLIC1 and IFITM2 expression in brain tissue correlates with cognitive impairment via immune dysregulation in sepsis and Alzheimer's disease.

BACKGROUND: Sepsis, a life-threatening condition driven by dysregulated host responses to infection,...

Development of machine learning models to predict the risk of fungal infection following flexible ureteroscopy lithotripsy.

BACKGROUND: The flexible ureteroscopy lithotripsy (F-URL) is an important treatment for upper urinar...

Assessing concordance between RNA-Seq and NanoString technologies in Ebola-infected nonhuman primates using machine learning.

This study evaluates the concordance between RNA sequencing (RNA-Seq) and NanoString technologies fo...

Clinical subtypes identification and feature recognition of sepsis leukocyte trajectories based on machine learning.

Sepsis is a highly variable condition, and tracking leukocyte patterns may offer insights for tailor...

Voice biomarkers as prognostic indicators for Parkinson's disease using machine learning techniques.

Many people suffer from Parkinson's disease globally, a complicated neurological condition caused by...

Machine learning approach for the prediction of 30-day mortality in patients with sepsis-associated delirium.

This study aimed to develop models for predicting the 30-day mortality of sepsis-associated delirium...

Febrile neutropenia management in high-risk neutropenic patients: a narrative review on antibiotic prophylaxis and empirical treatment.

INTRODUCTION: Although febrile neutropenia (FN) remains a major cause of morbidity and mortality in ...

C2BNet: A Deep Learning Architecture With Coupled Composite Backbone for Parasitic Egg Detection in Microscopic Images.

Internet of Medical Things (IoMT) enabled by artificial intelligence (AI) technologies can facilitat...

Direct-acting antivirals (DAA) positively affect depression and cognitive function in patients with chronic hepatitis C.

The aim of the study was to determine how depression and cognitive dysfunction in patients with chro...

A framework predicting removal efficacy of antibiotic resistance genes during disinfection processes with machine learning.

Disinfection has been applied widely for the removal of antibiotic resistance genes (ARGs) to curb t...

Characterization of Enterocytozoon hepatopenaei infection stages in shrimp using machine learning and gene network analysis.

Enterocytozoon hepatopenaei (EHP), causing hepatopancreatic microsporidiosis (HPM), significantly im...

Evolutionary learning in neural networks by heterosynaptic plasticity.

Training biophysical neuron models provides insights into brain circuits' organization and problem-s...

Integrating a host transcriptomic biomarker with a large language model for diagnosis of lower respiratory tract infection.

BACKGROUND: Lower respiratory tract infections (LRTIs) are a leading cause of mortality worldwide an...

Does infection alter antifungal distribution: an animal model exploring pharmacokinetic changes.

AIM: Assessing the disseminated meningitis caused by in Wistar rats and its impact on antifungal di...

Real-time surveillance system for patient deterioration: a pragmatic cluster-randomized controlled trial.

The COmmunicating Narrative Concerns Entered by RNs (CONCERN) early warning system (EWS) uses real-t...

Niuhuang jiedu prescription alleviates realgar-induced dopaminergic and GABAergic neurotoxicity in Caenorhabditis elegans.

ETHNOPHARMACOLOGICAL RELEVANCE: Niuhuang Jiedu (NHJD) is a Chinese medicine prescription containing ...

Artificial intelligence in hospital infection prevention: an integrative review.

BACKGROUND: Hospital-acquired infections (HAIs) represent a persistent challenge in healthcare, cont...

Harness machine learning for multiple prognoses prediction in sepsis patients: evidence from the MIMIC-IV database.

BACKGROUND: Sepsis, a severe systemic response to infection, frequently results in adverse outcomes,...

Constructing an early warning model for elderly sepsis patients based on machine learning.

Sepsis is a serious threat to human life. Early prediction of high-risk populations for sepsis is ne...

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