Critical Care

Sepsis

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

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A Hybrid Convolutional Neural Network Model for Diagnosis of COVID-19 Using Chest X-ray Images.

COVID-19 declared as a pandemic that has a faster rate of infection and has impacted the lives and t...

Adrenal Insufficiency in Septic Patients Admitted to Intensive Care Unit: Prevalence and Associated Factors.

Adrenal insufficiency (AI) is associated with an increase in the risk of mortality in ICU-admitted ...

Lactate levels as a prognostic predict in cardiogenic shock under venoarterial extracorporeal membrane oxygenation support.

INTRODUCTION AND OBJECTIVES: Lactate and its evolution are associated with the prognosis of patients...

Structure-Based Drug Design Using Deep Learning.

In recent years, deep learning-based methods have emerged as promising tools for drug design. Most ...

Proteome-Informed Machine Learning Studies of Cocaine Addiction.

No anti-cocaine addiction drugs have been approved by the Food and Drug Administration despite decad...

Machine learning implicates the IL-18 signaling axis in severe asthma.

Asthma is a common disease with profoundly variable natural history and patient morbidity. Heterogen...

Spatio-temporal prediction of the COVID-19 pandemic in US counties: modeling with a deep LSTM neural network.

Prediction of complex epidemiological systems such as COVID-19 is challenging on many grounds. Commo...

EpistoNet: an ensemble of Epistocracy-optimized mixture of experts for detecting COVID-19 on chest X-ray images.

The Coronavirus has spread across the world and infected millions of people, causing devastating dam...

A machine-learning parsimonious multivariable predictive model of mortality risk in patients with Covid-19.

The COVID-19 pandemic is impressively challenging the healthcare system. Several prognostic models h...

Susceptible-Infected-Removed Mathematical Model under Deep Learning in Hospital Infection Control of Novel Coronavirus Pneumonia.

OBJECTIVE: This research aimed to explore the application of a mathematical model based on deep lear...

DeepFlu: a deep learning approach for forecasting symptomatic influenza A infection based on pre-exposure gene expression.

BACKGROUND AND OBJECTIVE: Not everyone gets sick after an exposure to influenza A viruses (IAV). Alt...

A novel artificial intelligence based intensive care unit monitoring system: using physiological waveforms to identify sepsis.

A massive amount of multimodal data are continuously collected in the intensive care unit (ICU) alon...

Application of Deep Learning Models for Automated Identification of Parkinson's Disease: A Review (2011-2021).

Parkinson's disease (PD) is the second most common neurodegenerative disorder affecting over 6 milli...

Lipid peroxidation reduction and hippocampal and cortical neurons protection against ischemic damage in animal model using .

This study was aimed to determine the neuroprotective influence of in terms of restoring normal sta...

Using computers to ESKAPE the antibiotic resistance crisis.

Since the discovery of penicillin, the development and use of antibiotics have promoted safe and eff...

Predictive value of red blood cell distribution width in septic shock patients with thrombocytopenia: A retrospective study using machine learning.

BACKGROUND: Sepsis-associated thrombocytopenia (SAT) is common in critical patients and results in t...

Rapid identification of the resistance of urinary tract pathogenic bacteria using deep learning-based spectroscopic analysis.

The resistance of urinary tract pathogenic bacteria to various antibiotics is increasing, which requ...

Elevated Plasma von Willebrand Factor Levels Are Associated With Subsequent Ischemic Stroke in Persons With Treated HIV Infection.

BACKGROUND: We assessed whether key biomarkers of endothelial activation and hemostasis/thrombosis w...

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