Critical Care

Sepsis

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

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Showing 1660-1680 of 9,043 articles
Portable and intelligent ratio fluorometry and colorimetry for dual-mode detection of dopamine based on B, N-codoped carbon dots and machine learning.

A dual-mode approach was developed for dopamine (DA) assay based on boron (B) and nitrogen (N) co-do...

Supervised machine learning and molecular docking modeling to identify potential Anti-Parkinson's agents.

Parkinson's disease is a neurodegenerative condition that affects the brain's neurons, and causes ma...

Discrimination of Klebsiella pneumoniae and Klebsiella quasipneumoniae by MALDI-TOF Mass Spectrometry Coupled With Machine Learning.

Klebsiella species, including Klebsiella pneumoniae and Klebsiella quasipneumoniae, present signific...

Sepsis criteria and kidney function: eliminating sex, age and economic status biases.

The kidney is a target organ for the dysregulated host response to infection that defines sepsis, an...

A solution to the postantibiotic era: phages as precision medicine.

Antibiotic-resistant bacterial infections pose a significant global health challenge. Phage therapy ...

Decoding virulence and resistance in Klebsiella pneumoniae: Pharmacological insights, immunological dynamics, and in silico therapeutic strategies.

Klebsiella pneumoniae (K. pneumoniae) has become a serious global health concern due to its rising v...

Harnessing the fish gut microbiome and immune system to enhance disease resistance in aquaculture.

The increasing global reliance on aquaculture is challenged by disease outbreaks, exacerbated by ant...

Nutritionally Responsive PMv DAT Neurons Are Dynamically Regulated During Pubertal Transition.

Pubertal development is tightly regulated by energy balance. The crosstalk between metabolism and re...

Severe community-acquired pneumonia (sCAP): advances in management and future directions.

Severe community-acquired pneumonia (sCAP) is a major global health challenge, with high morbidity a...

Artificial intelligence based malignant lymphoma type prediction using enhanced super resolution image and hybrid feature extraction algorithm.

In the medical field, the most common and frequent type of blood cancer is lymphoma. Accurately pred...

Time-series deep learning and conformal prediction for improved sepsis diagnosis in primarily Non-ICU hospitalized patients.

PURPOSE: Sepsis, a life-threatening condition from an uncontrolled immune response to infection, is ...

Real-time FT-IR typing of Klebsiella pneumoniae: a flexible and rapid approach for outbreak detection and infection control.

BACKGROUND: Expansion of carbapenemase-producing Klebsiella pneumoniae (CP-Kp) is driven by within-h...

Predictive modeling of ARDS mortality integrating biomarker/cytokine, clinical and metabolomic data.

Acute Respiratory Distress Syndrome (ARDS), characterized by the rapid onset of respiratory failure ...

Speech signals-based Parkinson's disease diagnosis using hybrid autoencoder-LSTM models.

Parkinson's disease (PD) is a neurodegenerative disorder that occurs as a result of a decrease in th...

Identification and analysis of diagnostic markers related to lactate metabolism in myocardial infarction.

Lactate metabolism is implicated in myocardial infarction (MI), yet the underlying mechanisms are no...

A systematic methodological evaluation of sepsis guidelines: Protocol for quality assessment and consistency of recommendations.

BACKGROUND: Sepsis is a leading cause of mortality worldwide, characterized by a dysregulated host r...

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