Critical Care

Sepsis

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

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Showing 1786-1806 of 9,055 articles
Construction of a predictive model for rebleeding risk in upper gastrointestinal bleeding patients based on clinical indicators such as infection.

BACKGROUND: The annual incidence of upper gastrointestinal hemorrhage (UGIB) is about 60 cases/100,0...

Amphetamine use and Parkinson's disease: integration of artificial intelligence prediction, clinical corroboration, and mechanism of action analyses.

Parkinson's disease (PD) is an increasingly prevalent neurologic condition for which symptomatic, bu...

Machine learning for early prediction of the infection in patients with urinary stone after treatment of holmium laser lithotripsy.

Patients after holmium laser lithotripsy have a certain probability of getting postoperative infecti...

Segmentation-based lightweight multi-class classification model for crop disease detection, classification, and severity assessment using DCNN.

Leaf diseases in Zea mays crops have a significant impact on both the calibre and volume of maize yi...

Investigating the Impact of Antibiotics on Environmental Microbiota Through Machine Learning Models.

Antibiotic pollution in the environment can significantly impact soil microorganisms, such as alteri...

Microbial infection disease diagnosis and treatment by artificial intelligence.

OBJECTIVE: Aim: The main objective of this study was to examine current perspectives on initiatives ...

Artificial Intelligence in Endoscopy for Predicting Helicobacter pylori Infection: A Systematic Review and Meta-Analysis.

PURPOSE: This meta-analysis aimed to assess the diagnostic performance of artificial intelligence (A...

Artificial Intelligence Methods in Infection Biology Research.

Despite unprecedented achievements, the domain-specific application of artificial intelligence (AI) ...

Automated Evaluation of Antibiotic Prescribing Guideline Concordance in Pediatric Sinusitis Clinical Notes.

BACKGROUND: Ensuring antibiotics are prescribed only when necessary is crucial for maintaining their...

Machine learning-based infection diagnostic and prognostic models in post-acute care settings: a systematic review.

OBJECTIVES: This study aims to (1) review machine learning (ML)-based models for early infection dia...

SwinDFU-Net: Deep learning transformer network for infection identification in diabetic foot ulcer.

BACKGROUND: The identification of infection in diabetic foot ulcers (DFUs) is challenging due to var...

iACVP-MR: Accurate Identification of Anti-coronavirus Peptide based on Multiple Features Information and Recurrent Neural Network.

BACKGROUND: Over the years, viruses have caused human illness and threatened human health. Therefore...

SAMP: Identifying antimicrobial peptides by an ensemble learning model based on proportionalized split amino acid composition.

It is projected that 10 million deaths could be attributed to drug-resistant bacteria infections in ...

Applications of Machine Learning on Electronic Health Record Data to Combat Antibiotic Resistance.

There is growing excitement about the clinical use of artificial intelligence and machine learning (...

m6A-related genes and their role in Parkinson's disease: Insights from machine learning and consensus clustering.

Parkinson disease (PD) is a chronic neurological disorder primarily characterized by a deficiency of...

Machine learning-driven in-hospital mortality prediction in HIV/AIDS patients with infection: a single-centred retrospective study.

() is a widely disseminated betaherpesvirus that typically induces latant infections. In immunocom...

Can machine learning models improve the prediction of surgical site infection in abdominal surgery than traditional statistical models?

OBJECTIVE: To externally validate by revision and update the study on the efficacy of nosocomial inf...

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