Critical Care

Sepsis

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

7,154 articles
Stay Ahead - Weekly Sepsis research updates
Subscribe
Browse Categories
Critical-Care Subcategories: Sepsis
Showing 2878-2898 of 7,154 articles
Single time-point multi-dimensional biomarker models can predict acute organ injury trajectory

Forecasting acute organ injury trajectory remains a critical clinical challenge. Current approaches ...

From claims to care: Machine learning algorithm to classify urinary tract infection cases using Swiss health insurance data

To evaluate whether machine learning (ML) applied to comprehensive claims data without diagnostic co...

Personalized Fluid Management in Patients with Sepsis and AKI: A Casual Machine Learning Approach

Intravenous (IV) fluids are cornerstone for management of acute kidney injury (AKI) after sepsis but...

Forecasting trends of HIV infection using deep learning models in East Gojjam zone, North West Ethiopia, 2025

The growing burden of HIV/AIDS, particularly in sub-Saharan Africa, presents a significant public he...

Microscale Multiplexed Antigen-Specific Antibody Fc Profiling for Point-of-Care Diagnosis of Tuberculosis

Accurate, affordable tuberculosis (TB) diagnostics that do not require sputum samples are urgently n...

Dynamic Lymphocyte Recovery Patterns Predict 90-Day Mortality in Sepsis: A Machine Learning-Enhanced Analysis of the MIMIC-IV Cohort

Sepsis-induced immunosuppression, characterized by lymphopenia, is associated with adverse outcomes....

Prognostic role of COVID-19 pneumonia signs and other CT-biomarkers for survival in patients with malignant neoplasms: the ARILUS project

Clinically manifested pneumonia associated with COVID-19 infection in cancer patients has been assoc...

Predicting Carbapenem Resistance in Hospitalized Patients Using Machine Learning: A Retrospective Analysis of the MIMIC-III Database

Carbapenem-resistant Gram-negative bacteria (CR-GNB) represent a major health challenge due to limit...

Integrating Infection Burden and Multimodal Biomarkers for Early Detection of Alzheimers Disease: A Sheaf-ML Framework

Alzheimers disease (AD) remains a major global health challenge, with growing evidence linking chron...

From free text to SOFA score: automated reconstruction of sepsis severity from unstructured clinical notes

To evaluate the ability of a natural language processing system to automatically reconstruct the SOF...

Pandemic-Potential Viruses are a Blind Spot for Frontier Open-Source LLMs

We study large language models (LLMs) for front-line, pre-diagnostic infectious-disease triage, a cr...

Comparison of local large language models for extraction of signs and symptoms data from electronic health records

Electronic health records (EHRs) provide a large source of data that can be used for research purpos...

Single-Cell Nanomotion and Machine Learning for Parallel Bacterial Identification and Antibiotic Screening

Rapid and accurate identification of bacterial infections and their resistance to antibiotics is cri...

Browse Categories