Critical Care

Sepsis

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

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Critical-Care Subcategories: Sepsis
Showing 43-63 of 9,027 articles
Development of a risk prediction model for sepsis-related delirium based on multiple machine learning approaches and an online calculator.

BACKGROUND: Sepsis-associated delirium (SAD) occurs due to disruptions in neurotransmission linked t...

Machine learning to forecast rituximab responses for paediatric immune thrombocytopenia: Forging a path towards personalized medical care.

Primary immune thrombocytopenia (ITP) is an autoimmune disorder characterized by decreased platelet ...

APOE ε4 carriers share immune-related proteomic changes across neurodegenerative diseases.

The APOE ε4 genetic variant is the strongest genetic risk factor for late-onset Alzheimer's disease ...

Mortality and antibiotic timing in deep learning-derived surviving sepsis campaign risk groups: a multicenter study.

BACKGROUND: The current Surviving Sepsis Campaign (SSC) guidelines provide recommendations on timing...

A Machine Learning Approach to Microcalorimetric Pattern Classification of Pathogens in Synovial Fluid.

Isothermal microcalorimetry (IMC) is a promising tool for diagnosing periprosthetic joint infection ...

Computational exploration of global venoms for antimicrobial discovery with Venomics artificial intelligence.

The rise of antibiotic-resistant pathogens, particularly gram-negative bacteria, highlights the urge...

Machine learning-selected minimal features drive high-accuracy rule-based antibiotic susceptibility predictions for via metagenomic sequencing.

Antimicrobial resistance (AMR) represents a critical global health challenge, demanding rapid and ac...

Combating Antimicrobial Resistance: Role of Key Stakeholders with Focus on the Pharmaceutical Sector.

Antimicrobial resistance is a pressing global health threat fueled by a complex interplay of biologi...

SBC-SHAP: Increasing the Accessibility and Interpretability of Machine Learning Algorithms for Sepsis Prediction.

BACKGROUND: Sepsis is a life-threatening condition that is one of the major causes of death worldwid...

Image dataset of Taro Leaf Blight disease collected from the West African Sub-Region.

This dataset encompasses an extensive collection of 18,248 high-resolution JPEG images, documenting ...

Recent advancement in endoscopic diagnosis for risk stratification of gastric cancer.

Approximately 90% of cases of gastric cancer (GC) are caused by Helicobacter pylori infection, and s...

The application and discovery of animal models in enterovirus research.

Enterovirus infection remains a significant global public health challenge, causing severe diseases ...

Machine learning approaches to dissect hybrid and vaccine-induced immunity.

BACKGROUND: The spread of SARS-CoV-2 Omicron variant and its subvariants, highly transmissible but r...

Metabolic alterations driven by LDHA in CD8 + T cells promote immune evasion and therapy resistance in NSCLC.

Non-small cell lung cancer (NSCLC) is a leading cause of cancer-related deaths worldwide. Despite ad...

Citywide metagenomic surveillance of food centres reveals local microbial signatures and antibiotic resistance gene enrichment.

The distribution of microorganisms in built environments with high human traffic, such as food centr...

Identifying propionate metabolism-related genes as biomarkers of sepsis development and therapeutic targets.

The treatment of sepsis is challenging due to unclear mechanisms. Propionate is increasingly seen as...

CombiANT reader: Deep learning-based automatic image processing tool to robustly quantify antibiotic interactions.

Antibiotic resistance is a severe danger to human health, and combination therapy with several antib...

Machine Learning and DIA Proteomics Reveal New Insights into Carbapenem Resistance Mechanisms in .

The emergence of Carbapenem-resistant (CRKP) represents a major public health concern, primarily dr...

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