Critical Care

Sepsis

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

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Critical-Care Subcategories: Sepsis
Showing 295-315 of 9,027 articles
Point-annotation supervision for robust 3D pulmonary infection segmentation by CT-based cascading deep learning.

Infected region segmentation is crucial for pulmonary infection diagnosis, severity assessment, and ...

Integration of machine learning and meta-analysis reveals the behaviors and mechanisms of antibiotic adsorption on microplastics.

Microplastics (MPs) can adsorb antibiotics (ATs) to cause combined pollution in the environment. Res...

MSCMamba: Prediction of Antimicrobial Peptide Activity Values by Fusing Multiscale Convolution with Mamba Module.

Antimicrobial peptides (AMPs) have important developmental prospects as potential candidates for nov...

Autoregressive exogenous neural structures for synthetic datasets of olive disease control model with fractional Grünwald-Letnikov solver.

A fundamental element of the Mediterranean diet, olive oil is abundant in heart-healthy monounsatura...

Machine Learning Assisted-Intelligent Lactic Acid Monitoring in Sweat Supported by a Perspiration-Driven Self-Powered Sensor.

Lactic acid has aroused increasing attention due to its close association with serious diseases. A r...

Artificial intelligence using a latent diffusion model enables the generation of diverse and potent antimicrobial peptides.

Artificial intelligence holds great promise for the design of antimicrobial peptides (AMPs); however...

Constructing a machine learning model for systemic infection after kidney stone surgery based on CT values.

This study aims to develop a machine learning model utilizing Computed Tomography (CT) values to pre...

Neural mechanisms, influencing factors and interventions in empathic pain.

Empathic pain, defined as the emotional resonance with the suffering of others, is akin to the obser...

Machine Learning Tool for New Selective Serotonin and Serotonin-Norepinephrine Reuptake Inhibitors.

Depression, a serious mood disorder, affects about 5% of the population. Currently, there are two gr...

Elucidating the Mechanism of VVTT Infection Through Machine Learning and Transcriptome Analysis.

The vaccinia virus (VV) is extensively utilized as a vaccine vector in the treatment of various infe...

User-Oriented Requirements for Artificial Intelligence-Based Clinical Decision Support Systems in Sepsis: Protocol for a Multimethod Research Project.

BACKGROUND: Artificial intelligence (AI)-based clinical decision support systems (CDSS) have been de...

Leveraging machine learning to uncover multi-pathogen infection dynamics across co-distributed frog families.

BACKGROUND: Amphibians are experiencing substantial declines attributed to emerging pathogens. Effor...

Integrating Machine Learning with MALDI-TOF Mass Spectrometry for Rapid and Accurate Antimicrobial Resistance Detection in Clinical Pathogens.

Antimicrobial resistance (AMR) is one of the most pressing public health challenges of the 21st cent...

Identification of potential biomarkers for 2022 Mpox virus infection: a transcriptomic network analysis and machine learning approach.

Monkeypox virus (MPXV), a zoonotic pathogen, re-emerged in 2022 with the Clade IIb variant, raising ...

Leveraging AI-driven nudge theory to enhance hand hygiene compliance: paving the path for future infection control.

Hand hygiene is critical for preventing infections, yet maintaining compliance remains challenging a...

The clinical prediction model to distinguish between colonization and infection by .

OBJECTIVE: To develop a machine learning-based prediction model to assist clinicians in accurately d...

Colorimetric aptasensor coupled with a deep-learning-powered smartphone app for programmed death ligand-1 expressing extracellular vesicles.

Lung cancer is a devastating public health threat and a leading cause of cancer-related deaths. Ther...

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