Infectious Disease

Latest AI and machine learning research in infectious disease for healthcare professionals.

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Comparison of machine learning models to predict loss to follow-up among people with Human Immunodeficiency Virus (HIV).

OBJECTIVE: To compare different machine learning models of loss to follow-up among people with HIV (...

Single-cell image-based screens identify host regulators of Ebola virus infection dynamics.

Filoviruses such as Ebola virus (EBOV) give rise to frequent epidemics with high case fatality rates...

How to use learning curves to evaluate the sample size for malaria prediction models developed using machine learning algorithms.

BACKGROUND: Machine learning algorithms have been used to predict malaria risk and severity, identif...

Beyond labels: determining the true type of blood gas samples in ICU patients through supervised machine learning.

BACKGROUND: In the Intensive Care Unit (ICU), data stored in patient data management systems (PDMS) ...

Equity-enhanced glaucoma progression prediction from OCT with knowledge distillation.

Glaucoma is a progressive disease that can lead to permanent vision loss, making progression predict...

Artificially intelligent nasal perception for rapid sepsis diagnostics.

Sepsis, a life-threatening disease caused by infection, presents a major global health challenge due...

A variational deep-learning approach to modeling memory T cell dynamics.

Mechanistic models of dynamic, interacting cell populations have yielded many insights into the grow...

Classifying patients with invasive fungal disease: towards a unified case definition?

Management of invasive fungal disease (IFD) is increasingly challenging due to recognition of novel ...

Fast identification of influenza using label-free SERS combined with machine learning algorithms clinical nasal swab samples.

Influenza virus outbreaks, which have become more frequent in recent years, have attracted global at...

Multilevel Hydrangea-like Heterogeneous Oxides Enabling COVID-19 Progression Surveillance via Metabolic Fingerprints.

Coronavirus disease 2019 (COVID-19), a global pandemic infectious disease, requires early diagnosis ...

Unveiling the Role of Wetland Strategies in Antibiotic Risk Reduction across China by Machine Learning.

Pervasive antibiotic pollution in water environments has emerged as a serious threat to global ecosy...

A Machine Learning-Enabled SERS Sensor: Multiplex Detection of Lipopolysaccharides from Foodborne Pathogenic Bacteria.

Foodborne pathogenic bacteria pose a global threat to public health, causing dangerous and expensive...

Predicting delirium in critically Ill COVID-19 patients using EEG-derived data: a machine learning approach.

Delirium is a severe and common complication among critically ill patients, particularly those with ...

Non-invasive meningitis screening in neonates and infants: multicentre international study.

BACKGROUND AND OBJECTIVES: Meningitis diagnosis requires a lumbar puncture (LP) to obtain cerebrospi...

Global hotspots of mycorrhizal fungal richness are poorly protected.

Mycorrhizal fungi are ecosystem engineers that sustain plant life and help regulate Earth's biogeoch...

Explainable Temporal Inference for Irregular Multivariate Time Series. A Case Study for Early Prediction of Multidrug Resistance.

OBJECTIVE: Many healthcare problems involve complex patient trajectories represented as Multivariate...

Radiomics analysis for the early diagnosis of common sexually transmitted infections and skin lesions.

Early identification of sexually transmitted infection (STI) symptoms can prevent subsequent complic...

Machine learning in Alzheimer's disease genetics.

Traditional statistical approaches have advanced our understanding of the genetics of complex diseas...

Early detection of ICU-acquired infections using high-frequency electronic health record data.

BACKGROUND: Nosocomial infections are a major cause of morbidity and mortality in the ICU. Earlier i...

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