Critical Care

Sepsis

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

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Machine Learning-Guided Cobalt@Copper Dual-Metal Electrochemical Sensor for Urinary Creatinine Detection.

By utilizing the synergistic effects of a dual-metal cobalt@copper electrode and advanced machine le...

Bio inspired feature selection and graph learning for sepsis risk stratification.

Sepsis remains a leading cause of mortality in critical care settings, necessitating timely and accu...

A Chemistry-Informed Generative Deep Learning Approach for Enhancing Voltammetric Neurochemical Sensing in Living Mouse Brain.

Exploring the time-resolved dynamics of neurochemicals is essential for deciphering neuronal functio...

Prediction of bloodstream infection using machine learning based primarily on biochemical data.

Early diagnosis of bloodstream infection (BSI) is crucial for informed antibiotic use. This study de...

Optimal Vasopressin Initiation in Septic Shock: The OVISS Reinforcement Learning Study.

IMPORTANCE: Norepinephrine is the first-line vasopressor for patients with septic shock. When and wh...

Poisson random measure noise-induced coherence in epidemiological priors informed deep neural networks to identify the intensity of virus dynamics.

Differential equations-based epidemiological compartmental systems and deep neural networks-based ar...

RNA polymerase III transcription-associated polyadenylation promotes the accumulation of noncoding retrotransposons during infection.

UNLABELLED: The accumulation of RNA Polymerase III (Pol III) transcribed short interspersed nuclear ...

AI-based decoding of long covid cognitive impairments in mice using automated behavioral system and comparative transcriptomic analysis.

Long COVID (LC) following SARS-CoV-2 infection affects millions of individuals world-wide and manife...

MixOmics Integration of Biological Datasets Identifies Highly Correlated Variables of COVID-19 Severity.

Despite several years passing since the COVID-19 pandemic was declared, challenges remain in underst...

A Knowledge Graph for the Exploration of Human RSV Infection.

Despite decades of research and disease burden, RSV remains the most common cause of acute lower res...

Transforming Healthcare: The Role of Artificial Intelligence.

The integration of artificial intelligence (AI) into healthcare is revolutionising the industry by e...

Enhancing Clinical Decision Support: A Heuristic Evaluation of Explainable AI in Healthcare Dashboards.

Explainable Artificial Intelligence (XAI) is crucial for enhancing transparency, interpretability an...

Assessing Healthcare Stakeholder Understanding of Machine Learning Documentation.

Artificial Intelligence (AI) has significantly advanced clinical decision support systems in healthc...

SERS-ATB: A comprehensive database server for antibiotic SERS spectral visualization and deep-learning identification.

The rapid and accurate identification of antibiotics in environmental samples is critical for addres...

SERS based determination of ceftriaxone, ampicillin, and vancomycin in serum using WS/Au@Ag nanocomposites and a 2D-CNN regression model.

Accurate therapeutic drug monitoring (TDM) of antibiotics including ceftriaxone, ampicillin, and van...

Predicting sepsis treatment decisions in the paediatric emergency department using machine learning: the AiSEPTRON study.

BACKGROUND: Early identification of children at risk of sepsis in emergency departments (EDs) is cru...

Development and application of an early prediction model for risk of bloodstream infection based on real-world study.

BACKGROUND: Bloodstream Infection (BSI) is a severe systemic infectious disease that can lead to sep...

Tutorial: guidelines for the use of machine learning methods to mine genomes and proteomes for antibiotic discovery.

Genomes and proteomes constitute a rich reservoir of molecular diversity. However, they have remaine...

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