Critical Care

Sepsis

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

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Critical-Care Subcategories: Sepsis
Showing 253-273 of 9,027 articles
Hierarchical agent transformer network for COVID-19 infection segmentation.

Accurate and timely segmentation of COVID-19 infection regions is critical for effective diagnosis a...

Neuronal and therapeutic perspectives on empathic pain: A rational insight.

Empathy is the capacity to experience and understand the feelings of others, thereby playing a key r...

Advancing sepsis diagnosis and immunotherapy machine learning-driven identification of stable molecular biomarkers and therapeutic targets.

Sepsis represents a significant global health challenge, necessitating early detection and effective...

DRAMMA: a multifaceted machine learning approach for novel antimicrobial resistance gene detection in metagenomic data.

BACKGROUND: Antibiotics are essential for medical procedures, food security, and public health. Howe...

An AI-Based Clinical Decision Support System for Antibiotic Therapy in Sepsis (KINBIOTICS): Use Case Analysis.

BACKGROUND: Antimicrobial resistances pose significant challenges in health care systems. Clinical d...

Interpretable machine learning model for early morbidity risk prediction in patients with sepsis-induced coagulopathy: a multi-center study.

BACKGROUND: Sepsis-induced coagulopathy (SIC) is a complex condition characterized by systemic infla...

Measuring the Level of Aflatoxin Infection in Pistachio Nuts by Applying Machine Learning Techniques to Hyperspectral Images.

This paper investigates the use of machine learning techniques on hyperspectral images of pistachios...

Estimation of Ganciclovir Exposure in Adults Transplant Patients by Machine Learning.

INTRODUCTION: Valganciclovir, a prodrug of ganciclovir (GCV), is used to prevent cytomegalovirus inf...

New solutions for antibiotic discovery: Prioritizing microbial biosynthetic space using ecology and machine learning.

With the explosive increase in genome sequence data, perhaps the major challenge in natural-product-...

Targeting Bacterial RNA Polymerase: Harnessing Simulations and Machine Learning to Design Inhibitors for Drug-Resistant Pathogens.

The increase in antimicrobial resistance presents a major challenge in treating bacterial infections...

Contribution of Structure Learning Algorithms in Social Epidemiology: Application to Real-World Data.

Epidemiologists often handle large datasets with numerous variables and are currently seeing a growi...

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