Infectious Disease

Bacterial Infection

Latest AI and machine learning research in bacterial infection for healthcare professionals.

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Transformer-based long-term predictor of subthalamic beta activity in Parkinson’s disease

Deep brain stimulation (DBS) of the subthalamic nucleus (STN) is a mainstay treatment for patients w...

Unraveling the drivers of leptospirosis risk in Thailand using machine learning

Leptospirosis poses a significant public health challenge in Thailand, driven by a complex mix of en...

A mechanistic neural network model predicts both potency and toxicity of antimicrobial combination therapies

Antimicrobial resistance poses a major global threat due to the diminishing efficacy of current trea...

Utilizing Machine Learning Models to Predict Acute Kidney Injury in Septic Patients from MIMIC-III Database

Sepsis is a severe condition that causes the body to respond incorrectly to an infection. This react...

Prediction of the infecting organism in peritoneal dialysis patients with acute peritonitis using interpretable Tsetlin Machines

The analysis of complex biomedical datasets is becoming central to understanding disease mechanisms,...

Development of a Risk Prediction Model for Sepsis-Related Delirium Based on Multiple Machine Learning Approaches and an Online Calculator

Sepsis-associated delirium (SAD) occurs due to disruptions in neurotransmission linked to inflammato...

Conformal Prediction and Venn-ABERS Calibration for Reliable Machine Learning-Based Prediction of Bacterial Infection Focus

Finding the focus of bacterial infections can be challenging, especially for hospitalised patients. ...

Extracting TNFi Switching Reasons and Trajectories From Real-World Data Using Large Language Models

Tumor necrosis factor inhibitors (TNFi) are widely used for auto-immune conditions. Despite their ef...

Machine learning identifies clinical sepsis phenotypes that translate to the plasma proteome: a prospective cohort study

Sepsis therapy is still limited to treatment of the underlying infection and supportive measures. To...

Predicting Bacterial Vaginosis Development using Artificial Neural Networks

Bacterial vaginosis (BV) is a dysbiosis of the vaginal microbiome, characterized by the depletion of...

Plasma proteomics identifies molecular subtypes in sepsis

The heterogeneity of sepsis represents a significant challenge to the development of personalized se...

STM-GNN: Space-Time-and-Memory Graph Neural Networks for Predicting Multi-Drug Resistance Risks in Dynamic Patient Networks

Hospital-acquired infections (HAIs), particularly those caused by multidrug-resistant (MDR) bacteria...

Outbreak and Postnatal Antibiotic Exposures Drive the Development Trajectory of the Nasopharyngeal Microbiota in the First Year of Life

Early exposure to antibiotics and prolonged hospitalization in preterm infants may perturb microbiom...

Nucleotide motif-guided selection of plasma microRNA biomarkers for organ injury prediction in trauma

Trauma remains a leading cause of morbidity and mortality in part due to secondary organ injury and ...

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